72 Crewai Jobs

???? Senior AI/ML Engineer Multi-Agent & MCP Architect Location: Mumbai (Hybrid) Company: Fin 100X.AI Indias Protocol-Governed AI Financial OS ???? Company Description Fin 100X.AI is Indias first protocol-governed, AI-powered Financial Operating System built for Bharats 100 crore underserved citizens. We are reimagining finance through: Multi-agent AI orchestration (MCP protocol-driven) Explainable and trustworthy AI Regulatory-first design (RBI, SEBI, IRDAI, PFRDA aligned) Backed by IIT Bombay alumni and top fintech leaders, we are building AI for Bharat that blends technology, trust, and inclusion. ???? Role Overview As a Senior AI/ML Engineer (MCP + Multi-Agent Orchestration), you will be part of the founding tech braintrust that defines the core AI architecture of Fin 100X.AI. Your mission: Design and deploy a world-class, multi-agent AI stack powered by MCP (Model Context Protocol) to deliver scalable, explainable, and reliable AI-driven financial advisory modules for 100 crore users. You will directly influence: AI Laxmi orchestration Credit Booster, SIP Planner, Fraud Shield National-scale agentic financial intelligence ???? Key Responsibilities Architect and implement multi-agent AI systems using MCP protocol Build LLM orchestration pipelines (LangChain, AutoGen, CrewAI, MCP) Design retrieval-augmented pipelines (RAG) with vector memory & routing Deploy neural models (NLP, NLU, recommendation engines) at scale Create fallback, routing, and governance layers for explainable AI Integrate real-time financial intelligence APIs (OpenAI, Gemini, HuggingFace, etc.) Mentor junior AI engineers; enforce best practices in ML Ops and agent orchestration Collaborate with backend/frontend teams for end-to-end AI productionization ? Required Qualifications Core Technical Skills Strong foundation in ML/DL architectures, NLP, and LLMs Expertise in multi-agent orchestration frameworks: MCP, AutoGen, CrewAI, LangGraph Advanced experience with Python (TensorFlow, PyTorch, HuggingFace, FastAPI) Proficient in vector search systems (Pinecone, FAISS, ChromaDB) Deep knowledge of RAG pipelines, memory graphs, prompt chaining Experience deploying models in cloud-native and microservice architectures Preferred Exposure FinTech AI systems or regulated AI environments Agent evaluation, explainability, and safety-first design Scaling AI in hybrid production (cloud + edge) environments ???? What We Value Architect mindset with hands-on coding skills Self-driven innovation and ownership from concept ? deployment Experience building AI systems for 10M+ scale Passion for financial inclusion, Bharat-first AI, and AI for Good ???? Perks Shape Indias AI Financial OS from Day 0 ESOP track + leadership growth National showcase at Global FinTech Fest 2025 Mentorship with IIT Bombay alumni & top AI architects Solve real Bharat-scale problems with MCP-first AI innovation Show more Show less

As a US-based tech company with a global reach, DXFactor is renowned for being a certified Great Place to Work. Currently, we are seeking talented individuals for the position of AI Architect / Tech Lead AI at our Ahmedabad location. In this role, you will be at the forefront of developing a cutting-edge AI video marketing system that revolutionizes the traditional content creation process. The focus will be on leveraging AI technology to not only edit or repurpose content, but to generate, orchestrate, and deploy marketing content autonomously through AI agents. Your responsibilities will include designing Agentic AI Systems for Content Creation, where you will architect AI workflows that enable agents to collaborate in analyzing, scripting, editing, generating, and optimizing marketing videos using advanced technologies such as LLMs, vision models, and orchestration layers. Additionally, you will lead the development of Multi-Agent Pipelines by building intelligent systems that utilize frameworks like LangChain, AutoGen, or CrewAI to coordinate agents for various tasks such as scripting, visual editing, channel adaptation, voice/speech synthesis, and A/B testing. Moreover, you will apply AI to real-world video marketing use cases by using diverse content sources like UGC, branded, and influencer content to generate customized marketing assets suitable for different platforms. You will also be responsible for generating Synthetic Media when necessary, by integrating tools like Runway, Synthesia, Pika, or ElevenLabs to create or enhance content components. Furthermore, as the Lead Architect, you will be tasked with integrating AI systems with various components of the marketing stack including Content Management Systems (CSMs), Digital Asset Management (DAM) systems, ad tech APIs (Meta, TikTok, Google Ads), social platforms (YouTube, Instagram), and performance tools (Google Analytics, Segment, attribution platforms). Your role will encompass not only designing the architecture but also hands-on development, ensuring seamless integration and functionality across the marketing ecosystem.,

You are a skilled Data Engineer / AI/ML Developer with a strong expertise in Python and AI/ML, responsible for building and scaling production-grade systems using LLMs. Your role involves working on real-world AI integrations, APIs, and cloud deployments within a fast-paced, growth-focused team. Your key responsibilities include building AI/LLM systems using OpenAI, Anthropic, etc., working with frameworks like LangChain, CrewAI, or AutoGen, developing APIs with Flask/FastAPI and async patterns, integrating databases (PostgreSQL/MySQL) and REST APIs, deploying on AWS, GCP, or Azure, writing clean, testable, production-grade Python code, and translating business needs into technical solutions. To excel in this role, you must have 2+ years of experience with LLM APIs and 1+ AI project in production, 3+ years of Python development experience, familiarity with function calling, prompt design (ReAct, CoT), cloud deployment (any platform), Git workflows, and testing. Additionally, you should possess strong debugging, error handling, and system design skills, along with the ability to work independently and collaborate cross-functionally. A preferred background would include a degree in CS or equivalent experience (bootcamp, self-taught, etc.), along with a portfolio showcasing live AI projects or GitHub repos. Knowledge of Vector DBs (Pinecone/Weaviate), Docker, and exposure to fintech would be considered as a bonus. Cloud or AI certifications, as well as experience in fintech or data-heavy domains, are nice-to-have skills for this role.,

Project Overview We are seeking a Senior Agentic AI Engineer to lead the design and development of an enterprise-grade Agentic AI framework. This framework will empower various business units across the organization to build intelligent, autonomous agents capable of handling complex workflows, using tools, interacting with APIs, and making decisions with minimal human intervention.This role requires deep expertise in architecting scalable, modular AI systems using LLMs, tool integration, memory systems, and agent orchestration. This role is ideal for someone who has hands-on experience with agentic AI frameworks like LangGraph, CrewAI and AutoGPT and a deep understanding of enterprise software engineering and system architecture. Experience : 3.5 - 6 years Position : AI Engineer Skills Required : Python, Agentic AI, AI Models, Agentic Framework, Agentic Workflows, Langgraph OR CrewAI, Open source, data science Exposure Role and Responsibilities Architect and build a reusable, secure, and scalable Agentic AI framework that can be adopted by multiple teams across the enterprise. Define standards, patterns, and abstractions for building intelligent agents using LLMs and other foundational models. Leverage and extend frameworks like LangGraph, CrewAI, or Semantic Kernel to enable advanced agentic capabilities such as (Long-horizon task planning, Tool calling (APIs, databases, RPA, internal services), Memory persistence and retrieval (via vector stores or knowledge graphs),Autonomous decision-making and reflection,Multi-agent orchestration and collaboration, Human-in-the-loop workflows,Monitoring and observability,Governance and compliance,Security and access control,Performance optimization and cost management Collaborate with cross-functional teams to ensure the framework aligns with enterprise-grade expectations. Integrate the framework with existing enterprise platforms. Conduct research and stay updated on the latest advancements in Agentic AI, LLMs, and related technologies. Mentor and guide junior engineers in best practices for building agentic systems. Coach and guide engineering teams in adopting and extending the framework. Show more Show less

As an AI/ML Engineer Generative AI Specialist with over 5 years of experience, you will be expected to possess the following must-have skills: You should have a strong background in AI/ML frameworks such as PyTorch, TensorFlow, and proficient in Python programming. Your experience with AWS services, specifically AWS Bedrock and Lambda functions, will be crucial. Hands-on expertise in LangChain components (agents, chains, memories, parsers, document loaders), developing and optimizing GenAI, NLP models, and CrewAI is essential for this role. You should be capable of building and deploying RAG (Retrieval-Augmented Generation) systems, chatbots, and AI applications using OpenAI APIs, Ollama, Llama, and llamaparse. Advanced prompt engineering techniques like Chain of Thought (CoT) prompting should be within your skill set. Additionally, experience with Docker, CI/CD pipelines, YML files, and GitHub repository management is required. A strong understanding of system design principles, focusing on security, scalability, and performance optimization, is a must. Good-to-have skills include experience in responsible AI practices, knowledge of event-driven architecture, and familiarity with cloud deployments and Kubernetes. Experience with large-scale AI model training and fine-tuning would be beneficial. Your key responsibilities will involve designing and implementing AI/ML solutions using cutting-edge technologies to ensure scalability, efficiency, and alignment with business objectives. You will be responsible for developing and optimizing LangChain components, CrewAI, GenAI, and NLP models customized to specific applications. Building and deploying production-ready RAG systems, chatbots, and AI-driven applications utilizing OpenAI APIs, Ollama, Llama, and llamaparse will be part of your role. Leveraging AWS Bedrock and other AWS services to deliver high-performance AI solutions is crucial. You will need to apply prompt engineering techniques like Chain of Thought (CoT) prompting to enhance AI interactions, maintain CI/CD pipelines, manage YML files, and utilize GitHub for version control. Implementing containerization using Docker and deploying AI solutions in cloud environments will also fall under your responsibilities. Ensuring that solutions adhere to best practices in system design, focusing on security, performance, and efficiency considerations is essential. You will also need to incorporate responsible AI practices and ensure compliance with ethical AI guidelines. Collaboration with cross-functional teams to translate AI insights into impactful solutions and effective communication of complex technical concepts to both technical and non-technical stakeholders will be expected from you.,

Must Have Skills: 2+ years of hands-on experience in agentic AI / multi-agent systems. Proficiency with LangChain, Langraph, CrewAI, AutoGen, Haystack, or equivalent frameworks. Strong background in Python and experience with prompt engineering, tools integration, and chaining logic. Solid understanding of LLM APIs, RAG, vector stores, tool use, and memory architectures. Hands-on experience with open-source and commercial LLMs (e.g., GPT-4, Claude, Gemini, Mistral). Experience deploying AI agents in cloud-native environments (AWS, GCP, Azure). Ability to lead architectural discussions, PoCs, and hands-on development in fast-paced environments. Model-cost profiling and budgeting (API call minimization, batch vs. streaming) Latency tuning for real-time agents, Autoscaling strategies." Exposure to Autonomous AI agents (AutoGPT, BabyAGI, CAMEL, MetaGPT). Understanding of LLM fine-tuning, adapters, and RLHF. Experience with agent simulation, environment modeling, or reinforcement learning is a plus. Familiarity with compliance, privacy, and safety in GenAI deployments. Prior experience in building domain-specific agents (Lifescience, healthcare, Pharma). Key Responsibilities: Architect and implement agentic AI systems using modern LLM orchestration frameworks (LangChain, CrewAI, AutoGen, etc.). Design multi-agent collaboration models including planner-solver, autonomous teams, and goal decomposition agents. Build reusable tooling, APIs, and memory architectures for agent interaction, coordination, and context persistence. Lead hands-on development and deployment of GenAI applications (e.g., assistants, copilots, decision support). Evaluate and integrate LLMs (OpenAI, Claude, Mistral, LLaMA, etc.), vector databases (Pinecone, Weaviate, FAISS), and retrieval systems (RAG). Optimize agent performance for real-time environments, reliability, scalability, and ethical constraints. Guide teams in adopting agent frameworks, best practices, prompt engineering, and model fine-tuning. Collaborate with stakeholders to translate business requirements into technical solutions using agent-based paradigms. Continuously monitor trends in multi-agent systems, cognitive architectures, and open-source AI frameworks.

Mandatory Skills: 1. 5+ Years of experience in the design & development of state-of-the-art language models; utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. 2. Deep understanding of language models and a strong proficiency in designing and implementing RAG-based workflows to enhance content generation and information retrieval. 3. Experience in building, customizing and fine-tuning LLMs via OpenAI studio extended through Azure OpenAI cognitive services for rapid PoCs 4. Proven track record of successfully deploying and optimizing LLM models in the cloud (AWS, Azure, or GCP) for inference in production environments and proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization. 5. Apply prompt engineering techniques to design refined and contextually relevant prompts for language models. 6. Monitor and analyze the performance of LLMs by experimenting with various prompts, evaluating results, and refining strategies accordingly. 7. Building customizable, conversable AI agents for complex tasks using CrewAI and LangGraph to enhance Gen AI solutions 8. Proficient in MCP (Model Context Protocol) for optimizing context-aware AI model performance and integration is a plus Location - Mumbai , Pune, Bangalore, Chennai and Noida

Short Description Description About Oracle Customer Success Services Oracle University & the Role It is an exciting time to be part of Oracle Customer Success Services (CSS) Oracle University. As Oracle continues to rapidly introduce new products and enhancements, our focus is on delivering world class training solutions for next-generation AI capabilities that automate and revolutionize business processes across industries. The Fusion Cloud Applications Product Management Team within Oracle University is instrumental in setting the learner journey direction aligned to the innovative Fusion Cloud Applications AI initiative , and we are seeking a highly skilled, visionary Solution Lead with deep expertise in Oracle Fusion Cloud Applications and AI-driven solutions. This unique opportunity blends technical leadership, consulting, enablement, curriculum strategy, and hands-on innovation. You will shape, deliver, and educate on practical, scalable AI and AI Agent solutions that empower customers and Oracle partners to leverage leading AI capabilitieswhile translating the latest Oracle Fusion Cloud Application AI innovations into actionable training and enablement resources. Responsibilities Key Responsibilities AI Training Strategy and Design Lead the design and deployment of Oracle Fusion Cloud (ERP, HCM, SCM, CX) solutions by building and integrating the latest AI/ML innovations from Oracles evolving cloud portfolio into innovative training solutions. Consult closely with product development on the end-to-end implementation of practical AI agent applications, ensuring alignment with business objectives and industry best practices to include in OU training catalog. Serve as a subject matter expert and technical advisor, guiding customers and systems integrator partners on effectively implementing, tailoring, and operationalizing AI agent templates via OU training catalog. Advisory, & Best Practice Development Engage directly with Product Development to define training requirements, use cases, and desired AI outcomestranslating these needs into hands-on, deployable technical training solutions. Document and curate AI agent best practices, use cases, and lessons learned, elevating OU learners understanding and adoption of AI-powered enterprise solutions. Provide actionable feedback to CSS OU teams based on real-world AI agent deployments and customer interactions to continually evolve and enhance training. Partner & Customer Enablement: Training and Curriculum Leadership Act as an AI evangelist and enablement leaderdesign, develop, and continuously update comprehensive training curriculum and enablement resources focused on Oracle Fusion Cloud Applications AI capabilities for Oracle partners and customers. Proactively track and evaluate new Oracle Fusion Cloud AI features and innovations, translating advancements into high-impact internal and external enablement programs, workshops, documentation, and learning content. Innovation, Collaboration & Continuous Improvement Collaborate cross-functionally with Oracle product development and curriculum teams to innovate and refine agent-based cloud solutions, remaining hands-on and current in advanced AI and analytics trends. Lead continuous process and content improvement by gathering and analyzing stakeholder feedback, iterating training materials and curriculum as Oracles AI portfolio advances. Use project management and analytics tools to transparently track deliverables, monitor program and curriculum success, and measure overall business impact. Required Qualifications Bachelors or Masters degree in Computer Science, Software Engineering, Advanced Analytics, Information Systems, or a related STEM field. Experience working directly with customers, partners, and sales teams to deliver tailored technical solutions and advisory services Strong background in computer science, technical solution engineering, or advanced analytics. Understanding of RAG (Retrieval-Augmented Generation) techniques is required. Experience in designing and building AI multi-agent solutions for business environments is a plus Has built and deployed enterprise applications, including experience in solution engineering, building functional and/or technical demonstrations, consulting, or software development. Hands-on experience implementing scalable AI systems is desired though not required. Ability to understand, clarify, and translate functional/business requirements into practical, viable training solutions Experience leading Oracle Fusion Cloud Application implementations (ERP, HCM, SCM, CX) focusing on AI and enterprise innovation Demonstrated hands-on experience architecting, building, and deploying enterprise-class cloud and AI/ML solutionsparticularly within Oracle Fusion Cloud and/or analogous ERP, HCM, SCM, CX platforms. Expertise in the design of functional/technical curriculum and enablement material. Proficiency with frameworks such as Flowise, CrewAI, Relevance AI, Langchain, or AutoGen. Ability to consult, advise, and collaborate directly with enterprise customers, SI partners, and Oracle sales teams to deliver tailored, high-impact AI and cloud solutions. Outstanding communication skills (oral, written, and presentation), strong analytical and critical thinking skills, and the ability to proactively solve complex problems. Experience working in a fast-paced, dynamic software/cloud environment. Preferred Qualifications Oracle Cloud Architect and/or relevant Functional certifications. Experience enabling Oracle partners/customers in deploying and adopting AI or automation-driven cloud solutions. Previous involvement in change management and user adoption programs for enterprise systems. Knowledge of hybrid and multi-cloud architectures. Show more Show less

Backend Engineer (Python, Node Js, Agentic AI) Exp : 3 - 7 yrs Location: Pune Min 3 yrs exp in Backend developer exposure to AI/ML Min 2+ yrs exp in backend development using Python and Node.js For JD, write to amit.gaine@talentxo.in

The role involves working on Agentic AI Platform Delivery where you will be responsible for developing and maintaining autonomous software agents using modern LLM frameworks. You will also be required to build reusable components for business process automation, design agent orchestration, prompt engineering, and LLM integrations, as well as enable deployment across CRM systems and enterprise data platforms. Additionally, you will work on Generative AI & Model Optimization by fine-tuning LLMs/SLMs with proprietary NBFC data, and focusing on model distillation, quantization, and edge deployment readiness. Moreover, you will be creating self-learning systems by developing adaptive frameworks that learn from interaction outcomes and implementing lightweight models to support real-time decision-making. The ideal candidate for this position should hold a B.E./B.Tech/M.Tech degree in Computer Science or a related field, with a minimum of 3-7 years of experience in AI/ML roles. Proficiency in languages such as Python, Node.JS, JavaScript, React, and Java is required, along with experience in using tools/frameworks like LangChain, Semantic Kernel, LangGraph, and CrewAI. Familiarity with platforms such as GCP, MS Foundry, Copilot Studio, BigQuery, and Power Apps/BI is essential. Knowledge of Agent Tools like Agent Development Kit (ADK) and Multi-agent Communication Protocol (MCP), as well as a strong understanding of prompt engineering, LLM integration, and orchestration, are also expected. In addition to the technical requirements, the candidate should possess strong communication skills, teamwork abilities, and problem-solving capabilities. Being proactive, detail-oriented, and able to work under pressure are desirable traits for this role. Joining this dynamic team at Bajaj Finance Limited offers numerous perks, benefits, and a vibrant work culture. The company values its employees and recognizes their contributions, making it a rewarding and challenging environment to grow and excel. With a presence in over 500 locations across India, you will have the opportunity to be part of one of Asia's top 10 Large workplaces and contribute to the success and innovation of a leading Non-banking financial company.,

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Noida Location-3rd Aug 2025(Sunday) Interested candidates share your CV at umaparvathyc@hexaware.com Open Positions: AI Engineer/Lead Data Scientist (GenAI) AI Engineer Experience- 3+years Lead Data Scientist (GenAI) Experience- 7+years Notice Period- 15 days/30days Max (who serving Notice Period) Walkin Drive Location- Noida Date of drive- 3rd Aug 2025(Sunday) Must have Experience: LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Strong Experience in Data Scientist (GENAI) 2. Proficiency with Generative AI models like GANs, VAEs, and transformers 3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 4. Strong Python Fast API experience, SDA based implementations for all the APIs 5. Knowledge of Agentic AI concepts and applications

You will be part of a team that is building an Agentic AI Platform aimed at enabling enterprises to solve real business problems using Agentic AI workflows. The platform covers a wide range of areas from utility operations to legal document review. The ultimate goal is to empower AI agents to think, act, and deliver quickly, securely, and locally. As an Agentic AI Engineer, you will have the opportunity to work with cutting-edge frameworks such as Lang Chain, CrewAI, Lang Graph, Google ADK, and more. Your role will involve translating real enterprise challenges into intelligent multi-agent workflows. Your responsibilities will include building and deploying AI agents using open-source agentic frameworks, integrating models from sources like OpenAI, Mistral, Gemini, Llama, Claude, among others, and utilizing tools such as Retrieval-Augmented Generation (RAG), knowledge graphs, and vector stores. Collaboration with product managers and domain experts to address real problems in various enterprise domains like utilities, legal, marketing, and supply chain will be a key aspect of your role. Additionally, you will play a significant role in continuously testing and refining agent behavior and contributing to the enhancement of the proprietary DataInsightAI platform. To excel in this role, you should possess at least 1+ years of hands-on experience in implementing enterprise-level Gen AI projects that have been successfully deployed. Strong Python skills, familiarity with LLMs, agentic AI workflows, RAG, vector databases, and the ability to simplify complex problems are essential. A curiosity-driven mindset, a fast learner, and hands-on coding abilities are also crucial for success in this role. While not mandatory, experience in multi-agent architectures, graph databases like Neo4j, deployment on cloud platforms such as Azure/AWS/GCP, and familiarity with LangGraph or Google ADK are considered advantageous. Joining our team will offer you the opportunity to work on cutting-edge agentic AI projects daily, be part of a small team with significant ownership, ship solutions rapidly, and tackle real enterprise challenges. Moreover, you will be supported by InTimeTec, a company with a strong AI/ML engineering culture.,

You should have 3 to 10 years of experience in AI development and be located in Coimbatore. Immediate joiners are preferred. A minimum of 2 years of experience in core Gen AI is required. As an AI Developer, your responsibilities will include designing, developing, and fine-tuning Large Language Models (LLMs) for various in-house applications. You will implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Additionally, you will develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Building and managing data pipelines for processing, transforming, and feeding structured/unstructured data into AI models will be part of your role. It is essential to ensure scalability, performance, and security of AI-driven solutions in production environments. Collaboration with cross-functional teams, including data engineers, software developers, and product managers, is expected. You will conduct experiments and evaluations to improve AI system accuracy and efficiency while staying updated with the latest advancements in AI/ML research, open-source models, and industry best practices. You should have strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. Hands-on experience with RAG architectures, including vector databases such as Pinecone, ChromaDB, Weaviate, OpenSearch, and FAISS, is required. Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks is preferred. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow is necessary. Experience in Python web frameworks such as FastAPI, Django, or Flask is expected. You should also have experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark. Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes) is essential. Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications is a plus. A strong understanding of vector search, embedding models, and hybrid retrieval techniques is required. Experience with optimizing inference and serving AI models in real-time production systems is beneficial. Experience with multi-modal AI (text, image, audio) and familiarity with privacy-preserving AI techniques and responsible AI frameworks are desirable. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation, is a plus. Skills required for this role include PyTorch, RAG architectures, OpenSearch, Weaviate, Docker, LLM fine-tuning, ChromaDB, Apache Airflow, LoRA, Python, hybrid retrieval techniques, Django, GCP, CrewAI, OpenAI, Hugging Face, Gen AI, Pinecone, FAISS, AWS, AutoGPT, embedding models, Flask, FastAPI, LLM APIs, DeepSpeed, vector search, PEFT, LangChain, Azure, Spark, Kubernetes, AI Gen, TensorFlow, real-time production systems, LangGraph, and Kafka.,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

Work Location: Bangalore (in-office) We're seeking hands-on Lead Software Engineers who can: Build production-ready AI solutions on AWS Guide distributed teams while continuously scouting and prototyping emerging AI technologies You'll join our Product Engineering group, owning end-to-end delivery of next-generation Amorphic AI solutions while mentoring engineers across global teams. What is Expected: Technical Leadership Lead the integration of cutting-edge AI/LLMs into Amorphic AI Solutions, ensuring seamless interoperability and optimal performance Design and architect complex software systems with focus on scalability, maintainability, and performance Architect production-grade RAG pipelines and multi-agent orchestration on AWS (Lambda, ECS/Fargate, Bedrock, SageMaker, DynamoDB, S3, EventBridge, Step Functions) Drive the design and implementation of scalable AI pipelines Development & Innovation Design, develop, test, and maintain scalable backend applications using Python and AWS services Stay current with AI advancements through hands-on experimentation with emerging frameworks (LangChain, Hugging Face Transformers, CrewAI) via prototypes and side projects Optimize AI solution performance focusing on cost-effectiveness, latency, and resource utilization Develop strategies for monitoring, maintaining, and improving deployed AI models in production Team Leadership Lead 5-10 engineers through design reviews, pair-programming, and PR feedback Conduct code reviews and design discussions to ensure adherence to best practices Collaborate with cross-functional teams globally to identify requirements and implement solutions Create and maintain comprehensive documentation for architecture, design decisions, and coding practices Preferred Candidate Profile BE / B.Tech in Computer Science or related field 8+ years of experience in software development Solid understanding of large language models (LLMs), including experience with prompt engineering, fine-tuning, or integrating LLM APIs (e.g., from OpenAI, Anthropic, or AWS Bedrock) Hands-on experience building AI solutions using latest tools and frameworks (e.g., langchain, crewAI), demonstrated through side projects, open-source contributions, or personal prototypes Proven leadership experience in managing and mentoring high-performing teams of software and application developers Exceptional proficiency in Python programming language Solid understanding of AWS ecosystem including Lambda functions, S3 buckets, EMR clusters, DynamoDB tables etc. Proven experience in a leadership role, leading software development teams in the delivery of complex projects Deep understanding of software architecture and design principles, with a focus on building scalable and maintainable systems Experience with distributed systems, microservices architecture, and cloud-based solutions Strong knowledge of software development best practices, including code reviews, testing, and CI/CD pipelines Experience working with AWS services and developing Cloud Native Applications using REST APIs is must have Experience working in an agile delivery environment, especially product engineering teams How We'll Take Care Of You: We believe in supporting our team members both professionally and personally. Here's a look at the comprehensive benefits and perks we offer: Financial Well-being & Security Competitive Compensation : Enjoy competitive salaries and bonuses that reward your hard work and dedication Robust Insurance Coverage : Benefit from health, life, and disability insurance to ensure you and your family are protected Provident Fund Eligibility : Secure your future with eligibility for the provident fund Work-Life Balance & Flexibility Flexible Working Hours : We offer flexible working hours to help you manage your personal and professional commitments Generous Paid Time Off : Take advantage of unlimited Paid Time Off (PTO), with a mandatory minimum of 1 week per year to ensure you recharge Comprehensive Leave Policies : We provide paid vacation days, sick leave, and holidays, plus supportive parental leave (maternity, paternity, and adoption) and bereavement leave when you need it most Professional Growth & Development Learning & Development : Elevate your skills with access to extensive certification and training programs Cutting-Edge Technologies : You'll work at the forefront of innovation with cutting-edge technologies, constantly igniting your passion for continuous learning and growth Culture & Community Recognition & Rewards : Your contributions won't go unnoticed with our recognition and reward programs Engaging Activities : Connect with your colleagues through company-sponsored events, outings, team-building activities, and retreats .

We are looking for a Technical Architect who has experience designing software solutions from the ground up, making high-level decisions about each stage of the process and leading a team of engineers to create the final product. To be successful as a Technical Architect, you should be an expert problem solver with a strong understanding of the broad range of software technologies and platforms available. Top candidates will also be excellent leaders and communicators. Responsibilities Collaborate with stakeholders (Product Owners, Engineers, Clients) to define and refine software architecture aligned with product vision. Design scalable, modular, and secure system architecture using microservices and modern design patterns. Create high-level product specifications, architecture diagrams, and technical documentation. Provide architectural blueprints, guidance, and technical leadership to development teams. Build and integrate AI-driven components, including Agentic AI (AutoGen, LangGraph), RAG pipelines, and LLM capabilities (Open-source and Commercial models). Define vector-based data pipelines and integrate vector databases such as FAISS, ChromaDB, or Azure AI Search. Lead the implementation of Prompt Engineering strategies to optimize LLM outcomes. Architect and deploy scalable, secure solutions on Azure Cloud, using services like Azure Kubernetes Service (AKS), Azure Functions, Azure Storage, and Azure DevOps. Ensure robust CI/CD and DevSecOps practices in place to streamline deployments and enforce compliance. Guide the team in troubleshooting, code reviews, performance tuning, and ensuring adherence to software engineering best practices. Conduct regular technical reviews, present progress updates, and ensure timely delivery of milestones. Drive innovation and exploration of emerging technologies, particularly in the field of Generative AI and Intelligent Automation. Requirements 10+ years of hands-on software development experience, with a strong Python background. 3+ years of experience in a Software or Solution Architect role. Proven experience in designing and building production-grade solutions using microservices architecture. Strong expertise in Agentic AI frameworks (AutoGen, LangGraph, CrewAI, LangChain, etc.). Working knowledge of LLMs (Open-source like LLaMA, Mistral; Commercial like OpenAI, Azure OpenAI). Solid experience with Prompt Engineering, RAG pipelines, and Vector Database integration. Experience deploying AI/ML solutions on Azure Cloud, leveraging PaaS components and cloud-native patterns. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Knowledge of architectural patterns: event-driven, domain-driven design, CQRS, service mesh, etc. Familiarity with NLP tools, frameworks, and libraries (spaCy, Hugging Face, Transformers, etc.). Experience with Apache Airflow or other workflow orchestration tools. Strong communication and leadership skills to work cross-functionally with technical and non-technical teams.

58 years of experience in AI/ML or automation engineering. Strong hands-on experience with CrewAI or other LLM orchestration frameworks like LangChain, AutoGen, or Semantic Kernel. Proficiency in Python, including experience with async programming and API integration. Deep understanding of LLMs (OpenAI, Anthropic, Mistral, etc.) and prompt engineering. Familiarity with vector databases (e.g., Pinecone, FAISS, Chroma) and embeddings. Experience building and deploying production-ready agent-based solutions. Strong problem-solving skills and ability to translate business requirements into technical implementations.

As a candidate applying for this position, you should be prepared to attend face-to-face interviews and be open to the opportunity. The role offers a 5-day work week based in the office. Your responsibilities will include architecting and implementing REST APIs, designing and implementing high-performance applications with low latency, integrating GenAI-powered capabilities into backend systems, testing software for responsiveness and efficiency, collaborating with front-end developers, and troubleshooting application-related issues. You will also be expected to take initiatives in building efficient solutions for scalability and work closely with the infrastructure team in triaging major incidents. Additionally, you should have experience in analyzing and researching solutions, as well as developing and implementing recommendations accordingly. To qualify for this position, you should hold a Bachelor's Degree in Computer Science or a related field, along with a minimum of 4 years of professional experience. Expertise in JavaScript (ES6) and Node JS is essential, as well as a strong understanding of algorithms and data structures. Proficiency in frameworks like Express JS and Restify is required, along with experience in building backend services for handling large-scale data. You should be able to architect high-availability applications and servers on the cloud following best practices, with a preference for microservices architecture. Experience with MySQL, NoSQL databases like DynamoDB and MongoDB, as well as GenAI agentic frameworks is advantageous. Additionally, you should have experience with complex SQL queries, Node JS concepts, technical deep-dives into code, and building and deploying GenAI-powered backend services or tools. Understanding communication through WebSockets, clean architecture, SOLID principles, AWS, Docker containerization, Python, AI-assisted development tools, and Git is beneficial for this role. If you meet these requirements and are ready to take on these responsibilities, we welcome your application for this exciting opportunity.,

We are searching for a skilled and adaptable Data Engineer with proficiency in PySpark, Apache Spark, and Databricks, combined with knowledge in analytics, data modeling, and Generative AI/Agentic AI solutions. This position suits individuals who excel at the convergence of data engineering, AI systems, and business insights, contributing to impactful programs with clients. Your responsibilities will include designing, constructing, and enhancing distributed data pipelines utilizing PySpark, Apache Spark, and Databricks to cater to both analytics and AI workloads. You will also be tasked with supporting RAG pipelines, embedding generation, and data pre-processing for LLM applications. Additionally, creating and maintaining interactive dashboards and BI reports using tools like Power BI, Tableau, or Looker for business stakeholders and consultants will be part of your role. Furthermore, your duties will involve conducting adhoc data analysis to facilitate data-driven decision-making and rapid insight generation. You will be expected to develop and sustain robust data warehouse schemas, star/snowflake models, and provide support for data lake architecture. Integration with and support for LLM agent frameworks like LangChain, LlamaIndex, Haystack, or CrewAI for intelligent workflow automation will also fall under your purview. In addition, ensuring data pipeline monitoring, cost optimization, and scalability in cloud environments (Azure/AWS/GCP) will be important aspects of your work. Collaboration with cross-functional teams, including AI scientists, analysts, and business teams to drive use-case delivery, is key. Lastly, maintaining robust data governance, lineage, and metadata management practices using tools such as Azure Purview or DataHub will also be part of your responsibilities.,

Hi, Greetings from Sun Technology Integrators!! This is regarding a job opening with Sun Technology Integrators, Bangalore. Please find below the job description for your reference. Kindly let me know your interest and share your updated CV to nandinis@suntechnologies.com ASAP. Strong background in traditional AI/ML Experience building GenAI chatbots, agents, implementing tools with Gemini or similar vendors Fine tuning experience of LLMs Ability to work with LLM APIs Experience with modern Generative AI development frameworks and tools (LangChain, Vector DBs) Agentic Frameworks (e.g., LangGraph, CrewAI, ). Experience with prompt engineering Experience with RAG architecture Experience in Google Cloud and Vertex AI Experienced with Python Please let me know, if any of your friends are looking for a job change. Kindly share the references. Please Note: WFO- Work From Office (No hybrid or Work From Home) Shift Details: IST Shift - 12.30 PM to 9.30 PM IST -2 ways free cab facility(Pickup+Drop) Years of Exp-5 to 10 years Interview Mode- 2 rounds Virtual interview Thanks and Regards, Nandini S | Sr.Technical Recruiter Sun Technology Integrators Pvt. Ltd. nandinis@suntechnologies.com www.suntechnologies.com

Roles & Responsibilities GenAI Developer (5+ Years Experience) Minimum 5 years of overall experience , with at least 2 years of hands-on experience in building Generative AI (GenAI) solutions Strong working knowledge of Agentic AI frameworks , including experience in one or more of the following: LangGraph CrewAI Proven expertise in GenAI technologies , including: Python , LangChain , LangGraph , OpenAI APIs Azure Document Intelligence (ADI) Azure Service Bus Retrieval Augmented Generation (RAG) Experience in designing and implementing end-to-end GenAI applications with focus on scalability and enterprise-grade architecture Strong understanding of the Property & Casualty (P&C) Insurance domain and ability to apply GenAI solutions to relevant use cases Capable of integrating AI models with enterprise systems and APIs to build context-aware , intelligent applications Demonstrates clear communication skills , capable of working with technical and business stakeholders

5+ Years of experience in the design & development of state-of-the-art language models, Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Deep understanding of language models and a strong proficiency in designing and implementing RAG-based workflows to enhance content generation and information retrieval. Experience in building, customizing and fine-tuning LLMs via OpenAI studio extended through Azure OpenAI cognitive services for rapid PoCs Proven track record of successfully deploying and optimizing LLM models in cloud(AWS, Azure or GCP) for inference in production environments and proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization. Apply prompt engineering techniques to design refined and contextually relevant prompts for language models. Monitor and analyse the performance of LLMs by experimenting with various prompts, evaluating results, and refining strategies accordingly. Building customizable, conversable AI agents for complex tasks using CrewAI and LangGraph to enhance Gen AI solutions Proficient in MCP(Model Context Protocol) for optimizing context-aware AI model performance and integration is a plus Basic Qualifications: Bachelors or Masters degree in computer science or a related discipline. Good communication & Interpersonal skills to interact with customers and partner teams Must be a quick learner & Self-starter who requires minimal supervision. Excellent Problem solving, Critical thinking & Analytics skills. Proficiency in english(Oral & Written)

We are looking for a GenAI/ML Engineer to design, develop, and deploy cutting-edge AI/ML models and Generative AI applications . This role involves working on large-scale enterprise use cases, implementing Large Language Models (LLMs) , building Agentic AI systems , and developing data ingestion pipelines . The ideal candidate should have hands-on experience with AI/ML development , Generative AI applications , and a strong foundation in deep learning , NLP , and MLOps practices. Key Responsibilities Design, develop , and deploy AI/ML models and Generative AI applications for various enterprise use cases. Implement and integrate Large Language Models (LLMs) using frameworks such as LangChain , LlamaIndex , and RAG pipelines . Develop Agentic AI systems capable of multi-step reasoning and autonomous decision-making . Create secure and scalable data ingestion pipelines for structured and unstructured data, enabling indexing, vector search, and advanced retrieval techniques. Collaborate with cross-functional teams (Data Engineers, Product Managers, Architects) to deploy AI solutions and enhance the AI stack. Build CI/CD pipelines for ML/GenAI workflows and support end-to-end MLOps practices. Leverage Azure and Databricks for training , serving , and monitoring AI models at scale. Required Qualifications & Skills (Mandatory) 4+ years of hands-on experience in AI/ML development , including Generative AI applications . Expertise in RAG , LLMs , and Agentic AI implementations. Strong experience with LangChain , LlamaIndex , or similar LLM orchestration frameworks. Proficiency in Python and key ML/DL libraries : TensorFlow , PyTorch , Scikit-learn . Solid foundation in Deep Learning , Natural Language Processing (NLP) , and Transformer-based architectures . Experience in building data ingestion , indexing , and retrieval pipelines for real-world enterprise use cases. Hands-on experience with Azure cloud services and Databricks . Proven track record in designing CI/CD pipelines and using MLOps tools like MLflow , DVC , or Kubeflow . Soft Skills Strong problem-solving and critical thinking ability. Excellent communication skills , with the ability to explain complex AI concepts to non-technical stakeholders. Ability to collaborate effectively in agile , cross-functional teams . A growth mindset , eager to explore and learn emerging technologies. Preferred Qualifications Familiarity with vector databases such as FAISS , Pinecone , or Weaviate . Experience with AutoGPT , CrewAI , or similar agent frameworks . Exposure to Azure OpenAI , Cognitive Search , or Databricks ML tools . Understanding of AI security , responsible AI , and model governance . Role Dimensions Design and implement innovative GenAI applications to address complex business problems. Work on large-scale, complex AI solutions in collaboration with cross-functional teams. Take ownership of the end-to-end AI pipeline , from model development to deployment and monitoring. Success Measures (KPIs) Successful deployment of AI and Generative AI applications . Optimization of data pipelines and model performance at scale. Contribution to the successful adoption of AI-driven solutions within enterprise use cases. Effective collaboration with cross-functional teams, ensuring smooth deployment of AI workflows. Competency Alignment AI/ML Development : Expertise in building and deploying scalable and efficient AI models. Generative AI : Strong hands-on experience in Generative AI , LLMs , and RAG frameworks. MLOps : Proficiency in designing and maintaining CI/CD pipelines and implementing MLOps practices . Cloud Platforms : Experience with Azure and Databricks for AI model training and serving.

Prompt Engineering and its strategies Should know how LLM works and its hyper parameter ( temperature, top_p) Agentic AI framework like langchain, lang graph, crew ai RAG LLM evaluation and observability Python Deployment on any one of cloud services

As a part of the global leader in Cloud, AI, and Digital technologies, you will be responsible for leveraging GenAI models and frameworks to enhance the efficiency and productivity of businesses worldwide. Your role will involve serving as the primary technical expert for GenAI technologies, focusing on developing, implementing, and optimizing advanced AI models and solutions to expand our GenAI footprint across clients. You will provide technical leadership, drive innovation, and ensure the successful integration of AI technologies into our IT services for clients. Your responsibilities will include defining best practices, standards, and templates for AI solutions, conducting workshops, demos, and client presentations on GenAI use cases, and collaborating closely with cross-functional teams to identify, evaluate, and implement use cases across different customers. In addition, you will evaluate and integrate emerging GenAI technologies to enhance conversational AI capabilities, provide technical leadership, mentorship, and guidance to teams, troubleshoot and resolve complex platform integration and functionality issues. You will also be hands-on in independently building quick prototypes and demonstrating them to key decision-makers. To be successful in this role, you should have 10+ years of total IT experience with at least 3-4 years of hands-on experience with AI/GenAI technologies. Expertise in NLP, NLU, NLQ, and NLG technologies is essential, along with Core Python proficiency to build applications and engineer GenAI solutions at an enterprise scale. You must have delivered production-grade projects on agentic AI frameworks, as well as hands-on experience with agentic AI frameworks such as Autogen, Langraph, or Crew.AI. Experience with NLQ to SQL-based GenAI applications using core Python tools and frameworks, databases, data warehouses, and data lakes on cloud platforms is required. Deep knowledge of architecting product-scale GenAI applications on Microsoft Azure Cloud, AWS Cloud, or GCP cloud environments is a must. Strong programming skills in Python, Node.js, Java, or similar, API programming, familiarity with LLMs, prompt engineering, fine-tuning, and embeddings are desired. Excellent problem-solving skills, solution architecture capabilities, and client-facing communication skills are essential. The ability to translate business needs into technical solutions, manage multiple projects and priorities in a fast-paced environment, and work with cloud platforms is crucial. Moreover, expertise in building technical proposals with winning engineering architectures and technical articulation for CXO level audience, and experience in developing fast PoVs and blueprints on new and emerging GenAI models, tools, frameworks, and other stack will be advantageous for this role.,