63 Faiss Jobs

As a Python Developer specializing in Generative AI, you will play a key role in designing, developing, and deploying intelligent AI-powered systems during the night shift in Bangalore. Your primary responsibility will involve building and maintaining Python-based APIs and backends integrated with cutting-edge Generative AI models. You will collaborate with global teams to implement prompt engineering, fine-tuning, and model deployment pipelines using tools such as GPT, Claude, LLaMA, DALLE, and Stable Diffusion. Your expertise in PyTorch, TensorFlow, Hugging Face, LangChain, or OpenAI API will be crucial in optimizing model performance for latency, accuracy, and scalability. Additionally, you will deploy models using FastAPI, Flask, Docker, or cloud platforms while ensuring thorough testing, monitoring, and documentation of AI integrations. To excel in this role, you should possess at least 4 years of Python development experience along with 1 year of hands-on experience with Generative AI tools and models. Familiarity with vector databases such as FAISS, Pinecone, and Weaviate is also desirable. Exposure to GPU-based training or inference, MLOps tools like MLflow, Airflow, or Kubeflow, and a strong understanding of AI ethics, model safety, and bias mitigation are considered advantageous. This full-time, permanent position offers health insurance, Provident Fund benefits, and requires working in person during the night shift. If you are passionate about leveraging AI to address real-world challenges and thrive in a fast-paced environment, we encourage you to apply and contribute to innovative GenAI and ML projects.,

As a Python Backend Engineer specializing in AWS with a focus on GenAI & ML, you will be responsible for designing, developing, and maintaining intelligent backend systems and AI-driven applications. Your primary objective will be to build and scale backend systems while integrating AI/ML models using Django or FastAPI. You will deploy machine learning and GenAI models with frameworks like TensorFlow, PyTorch, or Scikit-learn, and utilize Langchain for GenAI pipelines. Experience with LangGraph will be advantageous in this role. Collaboration with data scientists, DevOps, and architects is essential to integrate models into production. You will be working with AWS services such as EC2, Lambda, S3, SageMaker, and CloudFormation for infrastructure and deployment purposes. Additionally, managing CI/CD pipelines for backend and model deployments will be a key part of your responsibilities. Ensuring the performance, scalability, and security of applications in cloud environments will also fall under your purview. To be successful in this role, you should have at least 5 years of hands-on experience in Python backend development and a strong background in building RESTful APIs using Django or FastAPI. Proficiency in AWS cloud services is crucial, along with a solid understanding of ML/AI concepts and model deployment practices. Familiarity with ML libraries like TensorFlow, PyTorch, or Scikit-learn is required, as well as experience with Langchain for GenAI applications. Experience with DevOps tools such as Docker, Kubernetes, Git, Jenkins, and Terraform will be beneficial. An understanding of microservices architecture, CI/CD workflows, and agile development practices is also desirable. Nice to have skills include knowledge of LangGraph, LLMs, embeddings, and vector databases, as well as exposure to OpenAI APIs, AWS Bedrock, or similar GenAI platforms. Additionally, familiarity with MLOps tools and practices for model monitoring, versioning, and retraining will be advantageous. This is a full-time, permanent position with benefits such as health insurance and provident fund. The work location is in-person, and the schedule involves day shifts from Monday to Friday in the morning. If you are interested in this opportunity, please contact the employer at +91 9966550640.,

???? 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

You will be joining a technology-driven publishing and legal-tech organization that is currently enhancing its capabilities through advanced AI initiatives. As an experienced AI Solution Architect, your role will involve leading the design, development, and deployment of transformative AI projects. You will work closely with a proficient internal team skilled in .NET, MERN, MEAN stacks, and recent chatbot development using OpenAI and LLaMA. Your responsibilities will include architecting, planning, and delivering enterprise-grade AI solutions utilizing Vector Databases like FAISS and Chroma, RAG Pipelines (Retrieval-Augmented Generation), and LLM techniques such as Pre-training, Fine-tuning, and RLHF (Reinforcement Learning with Human Feedback). You will lead AI solution design discussions, collaborate with engineering teams to integrate AI modules into systems, and guide junior AI engineers and developers on technical aspects. To excel in this role, you should hold a Bachelors or Masters in Computer Science, Engineering, AI/ML, or related fields and have at least 5 years of experience in software architecture with a focus on AI/ML system design and project delivery. Hands-on expertise in Vector Search Engines, LLM Tuning & Deployment, RAG systems, RLHF techniques, and working with multi-tech teams is essential. Strong command over architecture principles, scalability, microservices, API-based integration, and excellent team leadership skills are also required. It would be advantageous if you have experience with tools like MLflow, Weights & Biases, Docker, Kubernetes, Azure/AWS AI services, exposure to data pipelines, MLOps, AI governance, familiarity with enterprise software lifecycle, and DevSecOps practices. Prior experience in delivering a production-grade AI/NLP project with measurable impact is a plus. Stay updated on emerging AI trends and assess their relevance to business objectives to drive AI adoption across products and internal processes.,

We are looking for a Director of Engineering (AI Systems & Secure Platforms) to join our client&aposs Core Engineering team at Thane (Maharashtra - India). The ideal candidate should have 12-15+ years of experience in architecting and deploying AI systems at scale, with deep expertise in agentic AI workflows, LLMs, RAG, Computer Vision, and secure mobile/wearable platforms. Top 3 Daily Tasks: Architect, optimize, and deploy LLMs, RAG pipelines, and Computer Vision models for smart glasses and other edge devices. Design and orchestrate agentic AI workflowsenabling autonomous agents with planning, tool usage, error handling, and closed feedback loops. Collaborate across AI, Firmware, Security, Mobile, Product, and Design teams to embed "invisible intelligence" within secure wearable systems. Must have 12-15+ years of experience in Applied AI, Deep Learning, Edge AI deployment, Secure Mobile Systems, and Agentic AI Architecture. Must have: Programming languages: Python C/C++ Java Kotlin JavaScript/Node.js Swift Objective-C CUDA Shell scripting Expert in: TensorFlow PyTorch ONNX HuggingFace model optimization with TensorRT TFLite Deep experience with: LLMs RAG pipelines vector DBs (FAISS, Milvus) Proficient in agentic AI workflowsmulti-agent orchestration, planning, feedback loops Strong in privacy-preserving AI (federated learning, differential privacy) Secure real-time comms (WebRTC, SIP, RTP) Nice to have: Experience with MCP or similar protocol frameworks Background in wearables/XR or smart glass AI platforms Expertise in platform security architectures (sandboxing, auditability) Show more Show less

You will be part of a team that is developing an enterprise-grade, AI-powered agentic platform for the recruitment industry. Your role as a technical Co-Founder (CTO) will involve leading the development journey and defining the technical vision and architecture of the product from the ground up. Your responsibilities will include: - Defining and executing the technology strategy, roadmap, architecture, and infrastructure for a scalable, secure, and high-performing platform. - Leading hands-on development of the core platform, including AI agent integration, workflow automation, and data interaction layers. - Architecting and implementing LLM-based agentic features using tools like LangChain, OpenAI APIs, RAG pipelines, and vector databases. - Hiring, managing, and mentoring a high-performing engineering team across frontend, backend, ML, and DevOps. - Designing systems to handle large datasets, including data pipelines, analytics, and secure storage solutions. - Overseeing CI/CD pipelines, cloud infrastructure, monitoring, and cost-optimized deployments using AWS/GCP/Azure. The ideal candidate will have: - Proven experience in building and scaling enterprise-level web or mobile apps, preferably from 0 to 1. - Strong skills in Python/Django or Node.js, and modern JS frameworks such as React or Vue. - Deep experience with LLM integration, AI frameworks like LangChain and LlamaIndex, and vector databases like Pinecone and FAISS. - Solid understanding of database architecture, distributed systems, and API-first product development. - Past experience in leading or managing engineering teams. - Experience working in or co-founding an early-stage startup (preferred but not mandatory). Nice to have qualifications include: - Experience with multi-agent orchestration platforms like AutoGen, CrewAI, or AutoGPT. - Exposure to SaaS security, compliance, and data governance. - Knowledge of MLOps and deployment of AI models in production.,

As a Senior Data Scientist (Gen AI Developer) with 5 to 7+ years of experience, you will be based in Hyderabad and employed full-time in a hybrid work mode, spending 4 days in the office and 1 day working from home. Your primary responsibility will be to tackle a Conversational AI challenge for our client by utilizing your expertise in Speech-to-Text and Text Generation technologies. Your role will involve developing and fine-tuning Automatic Speech Recognition (ASR) models, implementing language models for industry-specific terminology, and incorporating speaker diarization to distinguish multiple voices in a conversation. Additionally, you will build conversation summarization models, apply Named Entity Recognition (NER), and use Large Language Models (LLMs) for deep conversation analysis and smart recommendations. You will also design Retrieval-Augmented Generation (RAG) pipelines leveraging external knowledge sources for enhanced performance. Furthermore, you will be tasked with creating sentiment and intent classification systems, developing predictive models for next-best-action suggestions based on historical call data and engagement, and deploying AI models on cloud platforms like AWS, Azure, or GCP. Optimizing inference and establishing MLOps pipelines for continual learning and performance enhancement will also be part of your responsibilities. To excel in this role, you must possess proven expertise in ASR, NLP, and Conversational AI systems, along with experience in tools such as Whisper, DeepSpeech, Kaldi, AWS Transcribe, and Google STT. Proficiency in programming languages like Python, PyTorch, TensorFlow, and familiarity with RAG, LangChain, and LLM fine-tuning is essential. Hands-on experience with vector databases and deploying AI solutions using Docker, Kubernetes, FastAPI, or Flask will be beneficial. Apart from technical skills, you should have strong business acumen to translate AI insights into impact, be a fast-paced problem-solver with innovative thinking abilities, and possess excellent collaboration and communication skills for effective teamwork across functions. Preferred qualifications include experience in healthcare, pharma, or life sciences NLP projects, knowledge of multimodal AI, prompt engineering, and exposure to Reinforcement Learning (RLHF) techniques for conversational models. Join us to work on impactful real-world projects in Conversational AI and Gen AI, collaborate with innovative teams and industry experts, leverage cutting-edge tools and cloud platforms, and enjoy a hybrid work environment that promotes flexibility and balance. Your ideas will be valued in our forward-thinking, AI-first culture. To apply for this exciting opportunity, please share your updated resume at resumes@empglobal.ae or apply directly through the platform. Kindly note that while we appreciate all applications, only shortlisted candidates will be contacted. Thank you for your understanding!,

As a Senior Machine Learning Engineer at our AI/ML team, you will be responsible for designing and building intelligent search systems. Your focus will be on utilizing cutting-edge techniques in vector search, semantic similarity, and natural language processing to create innovative solutions. Your key responsibilities will include designing and implementing high-performance vector search systems using tools like FAISS, Milvus, Weaviate, or Pinecone. You will develop semantic search solutions that leverage embedding models and similarity scoring for precise and context-aware retrieval. Additionally, you will be expected to research and integrate the latest advancements in ANN algorithms, transformer-based models, and embedding generation. Collaboration with cross-functional teams, including data scientists, backend engineers, and product managers, will be essential to bring ML-driven features from concept to production. Furthermore, maintaining clear documentation of methodologies, experiments, and findings for technical and non-technical stakeholders will be part of your role. To qualify for this position, you should have at least 3 years of experience in Machine Learning, with a focus on NLP and vector search. A deep understanding of semantic embeddings, transformer models (e.g., BERT, RoBERTa, GPT), and hands-on experience with vector search frameworks is required. You should also possess a solid understanding of similarity search techniques such as cosine similarity, dot-product scoring, and clustering methods. Strong programming skills in Python and familiarity with libraries like NumPy, Pandas, Scikit-learn, and Hugging Face Transformers are necessary. Exposure to cloud platforms, preferably Azure, and container orchestration tools like Docker and Kubernetes is preferred. This is a full-time position with benefits including health insurance, internet reimbursement, and Provident Fund. The work schedule consists of day shifts, fixed shifts, and morning shifts, and the work location is in-person. The application deadline for this role is 18/04/2025.,

We are looking for a Director of Engineering (AI Systems & Secure Platforms) to join our client&aposs Core Engineering team at Thane (Maharashtra India). The ideal candidate should have 1215+ years of experience in architecting and deploying AI systems at scale, with deep expertise in agentic AI workflows, LLMs, RAG, Computer Vision, and secure mobile/wearable platforms. 1. Top 3 Daily Tasks: - Architect, optimize, and deploy LLMs, RAG pipelines, and Computer Vision models for smart glasses and other edge devices. - Design and orchestrate agentic AI workflowsenabling autonomous agents with planning, tool usage, error handling, and closed feedback loops. - Collaborate across AI, Firmware, Security, Mobile, Product, and Design teams to embed invisible intelligence within secure wearable systems. 2. Must have: - Must have 1215+ years of experience in Applied AI, Deep Learning, Edge AI deployment, Secure Mobile Systems, and Agentic AI Architecture. Programming languages: Python C/C++ Java Kotlin JavaScript/Node.js Swift Objective-C CUDA Shell scripting - Expert in: TensorFlow PyTorch ONNX HuggingFace model optimization with TensorRT TFLite - Deep experience with: LLMs RAG pipelines vector DBs (FAISS, Milvus) - Proficient in agentic AI workflowsmulti-agent orchestration, planning, feedback loops - Strong in privacy-preserving AI (federated learning, differential privacy) - Secure real-time comms (WebRTC, SIP, RTP) 3. Nice to have: - Experience with MCP or similar protocol frameworks - Background in wearables/XR or smart glass AI platforms - Expertise in platform security architectures (sandboxing, auditability) Show more Show less

We seek a Senior AI Developer skilled in OpenAI (GPT-4/GPT-4o) and Google Gemini to build advanced AI apps and agents. You'll lead LLM integrations, RAG pipelines, and GenAI solutions across industries in a fast-paced, innovative product team. Required Candidate profile 4+ yrs dev exp in GenAI/LLMs. Proficient in OpenAI, Gemini, Python, LangChain, vector DBs. Strong in RAG, prompt engineering, chatbot, cloud. Bonus: experience with Whisper, Gemini Pro, Hugging Face

You will be joining a technology-driven publishing and legal-tech organization that is currently expanding its capabilities through advanced AI initiatives. With a strong internal team proficient in .NET, MERN, MEAN stacks, and recent chatbot development using OpenAI and LLaMA, we are seeking an experienced AI Solution Architect to lead the design, development, and deployment of transformative AI projects. As an AI Solution Architect, you will play a critical role in designing and delivering enterprise-grade AI solutions. Your responsibilities will include architecting, planning, and implementing AI solutions using Vector Databases, RAG Pipelines, and LLM techniques. You will lead AI solution design discussions, collaborate with engineering teams to integrate AI modules, evaluate AI frameworks, and mentor junior AI engineers and developers. To excel in this role, you should have a Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or related fields, along with at least 5 years of experience in software architecture with a focus on AI/ML system design and project delivery. Hands-on expertise in Vector Search Engines, LLM Tuning & Deployment, RAG systems, and RLHF techniques is essential. You should also have experience working with multi-tech teams, strong command over architecture principles, and excellent team leadership skills. Experience with tools like MLflow, Weights & Biases, Docker, Kubernetes, and Azure/AWS AI services would be a plus. Exposure to data pipelines, MLOps, and AI governance, as well as familiarity with enterprise software lifecycle and DevSecOps practices, are also desirable. If you are passionate about AI technology, have a proven track record of delivering AI projects, and enjoy leading and mentoring technical teams, we encourage you to apply for this exciting opportunity to drive AI adoption across products and internal processes.,

As a Senior Python Engineer at our company, you will leverage your deep expertise in data engineering and API development to drive technical excellence and autonomy. Your primary responsibility will be leading the development of scalable backend systems and data infrastructure that power AI-driven applications across our platform. You will design, develop, and maintain high-performance APIs and microservices using Python frameworks such as FastAPI and Flask. Additionally, you will build and optimize scalable data pipelines, ETL/ELT processes, and orchestration frameworks, ensuring the utilization of AI development tools like GitHub Copilot, Cursor, or CodeWhisperer to enhance engineering velocity and code quality. In this role, you will architect resilient and modular backend systems integrated with databases like PostgreSQL, MongoDB, and Elasticsearch. Managing workflows and event-driven architectures using tools such as Airflow, Dagster, or Temporal.io will be essential, as you collaborate with cross-functional teams to deliver production-grade systems in cloud environments (AWS/GCP/Azure) with high test coverage, observability, and reliability. To be successful in this position, you must have at least 5 years of hands-on experience in Python backend/API development, a strong background in data engineering, and proficiency in AI-enhanced development environments like Copilot, Cursor, or equivalent tools. Solid experience with Elasticsearch, PostgreSQL, and scalable data solutions, along with familiarity with Docker, CI/CD, and cloud-native deployment practices is crucial. You should also demonstrate the ability to take ownership of features from idea to production. Nice-to-have qualifications include experience with distributed workflow engines like Temporal.io, background in AI/ML systems (PyTorch or TensorFlow), familiarity with LangChain, LLMs, and vector search tools (e.g., FAISS, Pinecone), and exposure to weak supervision, semantic search, or agentic AI workflows. Join us to build infrastructure for cutting-edge AI products and work in a collaborative, high-caliber engineering environment.,

We are looking for a Director of Engineering (AI Systems & Secure Platforms) to join our client&aposs Core Engineering team at Thane (Maharashtra India). The ideal candidate should have 1215+ years of experience in architecting and deploying AI systems at scale, with deep expertise in agentic AI workflows, LLMs, RAG, Computer Vision, and secure mobile/wearable platforms. Top 3 Daily Tasks: ? Architect, optimize, and deploy LLMs, RAG pipelines, and Computer Vision models for smart glasses and other edge devices. ? Design and orchestrate agentic AI workflowsenabling autonomous agents with planning, tool usage, error handling, and closed feedback loops. ? Collaborate across AI, Firmware, Security, Mobile, Product, and Design teams to embed invisible intelligence within secure wearable systems. Must have 1215+ years of experience in Applied AI, Deep Learning, Edge AI deployment, Secure Mobile Systems, and Agentic AI Architecture. Must have: -Programming languages: Python, C/C++, Java (Android), Kotlin, JavaScript/Node.js, Swift, Objective-C, CUDA, Shell scripting -Expert in TensorFlow, PyTorch, ONNX, HuggingFace; model optimization with TensorRT, TFLite -Deep experience with LLMs, RAG pipelines, vector DBs (FAISS, Milvus) -Proficient in agentic AI workflowsmulti-agent orchestration, planning, feedback loops -Strong in privacy-preserving AI (federated learning, differential privacy) -Secure real-time comms (WebRTC, SIP, RTP) Nice to have: -Experience with MCP or similar protocol frameworks -Background in wearables/XR or smart glass AI platforms -Expertise in platform security architectures (sandboxing, auditability) Industry Technology, Information and Internet Employment Type Full-time Show more Show less

About the Role We are seeking a BI Architect to advise the BI Lead of a global CPG organization and architect an intelligent, scalable Business Intelligence ecosystem. This includes an enterprise-wide KPI dashboard suite augmented by a GenAI-driven natural language interface for insight discovery. The ideal candidate will be responsible for end-to-end architecture: from scalable data models and dashboards to a conversational interface powered by Retrieval-Augmented Generation (RAG) and/or Knowledge Graphs. The solution must synthesize internal BI data with external (web-scraped and competitor) data to deliver intelligent, context-rich insights. Key Responsibilities • Architect BI Stack : Design and oversee a scalable and performant BI platform that serves as a single source of truth for key business metrics across functions (Sales, Marketing, Supply Chain, Finance, etc.). • Advise BI Lead : Act as a technical thought partner to the BI Lead, aligning architecture decisions with long-term strategy and business priorities. • Design GenAI Layer : Architect a GenAI-powered natural language interface on top of BI dashboards to allow business users to query KPIs, trends, and anomalies conversationally. • RAG/Graph Approach : Select and implement appropriate architectures (e.g., RAG using vector stores, Knowledge Graphs) to support intelligent, context-aware insights. • External Data Integration : Build mechanisms to ingest and structure data from public sources (e.g., competitor websites, industry reports, social sentiment) to augment internal insights. • Security & Governance : Ensure all layers (BI + GenAI) adhere to enterprise data governance, security, and compliance standards. • Cross-functional Collaboration : Work closely with Data Engineering, Analytics, and Product teams to ensure seamless integration and operationalization. Qualifications • 69 years of experience in BI architecture and analytics platforms, with at least 2 years working on GenAI, RAG, or LLM-based solutions. • Strong expertise in BI tools (e.g., Power BI, Tableau, Looker) and data modeling. • Experience with GenAI frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) and vector databases (e.g., Pinecone, FAISS, Weaviate). • Knowledge of graph-based data models and tools (e.g., Neo4j, RDF, SPARQL) is a plus. • Proficiency in Python or relevant scripting language for pipeline orchestration and AI integration. • Familiarity with web scraping and structuring external/third-party datasets. • Prior experience in CPG domain or large-scale KPI dashboarding preferred.

You will be joining a company that is renowned for its technical excellence and leading innovations. NTT DATA is committed to making a difference to clients and society while embracing diversity and inclusion in the workplace. It is a place where you can grow, belong, and thrive. As a Senior AI/GenAI Engineer at NTT DATA, your key responsibilities will include designing, developing, and deploying cutting-edge AI/GenAI models and solutions for various industries. You will utilize technologies such as TensorFlow, PyTorch, LangChain, Vellum, etc., on non-cloud infrastructure. Your role will involve leading the development and integration of agentic AI systems, designing vector databases for efficient similarity search in AI applications, providing technical guidance to junior team members, ensuring security of LLMs, engaging with clients to understand their AI requirements, developing tailored solutions, and more. Requirements for this role include a Bachelor's or Master's degree in Computer Science, AI, ML, or related fields, along with 8+ years of experience in engineering solutions and delivering AI solutions. You should have advanced proficiency in AI/GenAI technologies, experience with vector databases and similarity search algorithms, strong programming skills in languages like Python or R, excellent communication and interpersonal skills, and strong problem-solving abilities. It is preferred that you have experience with containerization (Docker) and orchestration (Kubernetes), as well as experience with ReactJS for rapid prototyping. The position is available in Delhi or Bangalore, with a hybrid working model. NTT DATA is a global innovator of business and technology services, serving 75% of the Fortune Global 100. The company is committed to helping clients innovate, optimize, and transform for long-term success. NTT DATA invests over $3.6 billion each year in R&D and offers services including business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation, and management of applications, infrastructure, and connectivity. NTT DATA is an Equal Opportunity Employer and part of the NTT Group headquartered in Tokyo.,

You are an experienced Python Backend Engineer with a strong background in AWS and AI/ML. Your primary responsibility will be to design, develop, and maintain Python-based backend systems and AI-powered services. You will be tasked with building and managing RESTful APIs using Django or FastAPI for AI/ML model integration. Additionally, you will develop and deploy machine learning and GenAI models using frameworks like TensorFlow, PyTorch, or Scikit-learn. Your expertise in implementing GenAI pipelines using Langchain will be crucial, and experience with LangGraph is considered a strong advantage. You will leverage various AWS services such as EC2, Lambda, S3, SageMaker, and CloudFormation for infrastructure and deployment purposes. Collaborating with data scientists, DevOps, and architects to integrate models and workflows into production will be a key aspect of your role. Furthermore, you will be responsible for building and managing CI/CD pipelines for backend and model deployments. Ensuring the performance, scalability, and security of applications in cloud environments will be paramount. Monitoring production systems, troubleshooting issues, and optimizing model and API performance will also fall under your purview. To excel in this role, you must possess at least 5 years of hands-on experience in Python backend development. Your strong experience in building RESTful APIs using Django or FastAPI is essential. Proficiency in AWS cloud services, a solid understanding of ML/AI concepts, and experience with ML libraries are prerequisites. Hands-on experience with Langchain for building GenAI applications and familiarity with DevOps tools and microservices architecture will be beneficial. Additionally, having Agile development experience and exposure to tools like Docker, Kubernetes, Git, Jenkins, Terraform, and CI/CD workflows will be advantageous. Experience with LangGraph, LLMs, embeddings, and vector databases, as well as knowledge of MLOps tools and practices, are considered nice-to-have qualifications. In summary, as a Python Backend Engineer with expertise in AWS and AI/ML, you will play a vital role in designing, developing, and maintaining intelligent backend systems and GenAI-driven applications. Your contributions will be instrumental in scaling backend systems and implementing AI/ML applications effectively.,

You are an experienced AI Engineer who will be a valuable addition to our team in developing and integrating cutting-edge AI tools into our SaaS products. Your expertise with platforms like OpenAI, LangChain, or Hugging Face, coupled with a strong background in delivering scalable, production-ready AI solutions, will be key in this role. As the AI Engineer, you will lead AI feature development, collaborate cross-functionally, and mentor junior engineers. Your responsibilities will include designing and developing AI-driven features leveraging large language models (LLMs) and embedding techniques. You will integrate solutions using tools such as OpenAI, vector databases (e.g., Pinecone, FAISS), and generative AI frameworks like LangChain or Hugging Face. Additionally, you will build and maintain Retrieval-Augmented Generation (RAG) pipelines and conversational AI workflows, collaborating closely with backend and frontend engineering teams to ensure seamless integration of AI capabilities into the product. Continuous optimization of AI models and pipelines for performance, scalability, and accuracy will also be part of your role. To be successful in this position, you should have at least 3-5 years of experience in AI/ML-focused software development, proficiency in Python, and hands-on experience with AI frameworks and toolkits such as LangChain, Pinecone, and OpenAI. Strong problem-solving abilities, a solid understanding of system architecture and design, as well as excellent communication and collaboration skills are essential requirements. This is a full-time position with benefits including food provision, health insurance, and Provident Fund. The work schedule is day shift, Monday to Friday, with the work location being in person.,

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.,

The Senior Data Science Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. Key Responsibilities: 1. Architecting & Scaling Agentic AI Solutions: - Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. - Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. - Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization: - Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. - Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. - Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research: - Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. - Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. - Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact: - Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. - Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building: - Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. - Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents.,

As a skilled and visionary AI Lead at Matellio, you will be responsible for driving the development of advanced AI solutions. This dual role will require you to provide technical leadership and hands-on development expertise, making it an ideal position for individuals who excel at solving complex problems using machine learning, NLP, and LLM technologies. Your key responsibilities will include leading and mentoring a team of 45 AI/ML engineers, overseeing the entire project lifecycle from research to production deployment. You will be tasked with designing and owning high-level and low-level architecture for AI and GenAI-based applications, ensuring scalability, performance, and maintainability. Collaboration with sales and business development teams to create technical proposals, solution designs, and architecture diagrams for Sales Qualified Leads (SQLs) will also be part of your role. Additionally, you will work as an individual contributor when necessary, focusing on developing key components of solutions to accelerate delivery and establish best practices. Your responsibilities will extend to researching, designing, and implementing machine learning and deep learning models, including fine-tuning and deploying LLMs like GPT and BERT for production use cases. Building NLP pipelines and retrieval-augmented generation (RAG) systems using tools such as LangChain, LangGraph, and vector databases like FAISS, Pinecone, and Weaviate will also be crucial. You will be expected to apply statistical techniques to feature engineering, model evaluation, and performance optimization, ensuring adherence to code quality, testing, CI/CD, and documentation standards. Staying up-to-date with the latest advancements in AI/ML and proposing innovative solutions will be essential. Conducting code reviews, promoting peer learning, and fostering a strong engineering culture will also be part of your responsibilities. To qualify for this role, you should hold a Bachelors, Masters, or Ph.D. in Computer Science, Engineering, Mathematics, or a related field. Additionally, you should have at least 7 years of hands-on experience in AI/ML model development and deployment. Proven expertise in leading technical teams and delivering production-grade AI/ML solutions is required. Strong architectural skills with experience in designing end-to-end solutions involving cloud, APIs, and ML models are essential. Proficiency in Python and ML libraries such as TensorFlow, PyTorch, and scikit-learn is necessary, along with hands-on experience in NLP tools like HuggingFace Transformers, SpaCy, and NLTK. Practical knowledge of fine-tuning and deploying LLMs, as well as building GenAI solutions, is expected. Familiarity with tools like LangChain, LangGraph, and vector stores (e.g., FAISS, Pinecone) will be advantageous. A solid understanding of classical ML algorithms (SVM, Decision Trees, etc.) and when to utilize them, experience deploying models and services using REST APIs, Docker, and CI/CD pipelines, and exposure to cloud platforms such as AWS, GCP, or Azure are highly desirable. Excellent analytical thinking, problem-solving, and communication skills will be crucial for success in this role.,

As a Backend Developer, your primary responsibility will be to develop and maintain backend services using Python, with a strong emphasis on FastAPI, NumPy, and Polars for efficient handling of data. You will be tasked with building and managing agentic workflows utilizing LangChain, LangGraph, and MCP Agents to facilitate dynamic, multi-step reasoning. Additionally, you will design and execute RAG pipelines for contextual information retrieval and response generation. Integration and optimization of MongoDB or similar vector databases like FAISS and Pinecone for semantic search and embedding storage will also fall under your purview. Collaboration with cross-functional teams to deploy scalable AI services in production will be a crucial part of your role. Furthermore, you will be responsible for conducting performance tuning, testing, and deployment of AI components, while also keeping abreast of the latest developments in GenAI, LLMs, and agentic architectures. The ideal candidate for this position should possess a minimum of 3-6 years of experience in backend development using Python. You should have hands-on experience with FastAPI for constructing RESTful APIs, as well as proficiency in NumPy and Polars for numerical and tabular data processing. A solid understanding of Generative AI concepts is essential, along with practical experience in working with LangChain, LangGraph, and MCP Agents. Experience in building and deploying agentic RAG systems and familiarity with MongoDB or other vector databases for semantic search and retrieval will be advantageous. Knowledge of cloud platforms such as Azure and containerization tools like Docker/Kubernetes will be considered a plus. To qualify for this role, you should hold a Bachelors or Masters degree in computer science, data science, mathematics, or a related field.,

As a Senior Data Engineer + AI, you will play a crucial role in designing and optimizing distributed data pipelines using PySpark, Apache Spark, and Databricks to cater to both analytics and AI workloads. Your expertise in PySpark, Apache Spark, and Databricks for batch and streaming data pipelines will be instrumental in contributing to high-impact programs with clients. Your strong SQL skills for data analysis, transformation, and modeling will enable you to drive data-driven decision-making and facilitate rapid insight generation. Your responsibilities will involve supporting RAG pipelines, embedding generation, and data pre-processing for LLM applications, as well as creating and maintaining interactive dashboards and BI reports using tools such as Power BI, Tableau, or Looker. You will collaborate with cross-functional teams, including AI scientists, analysts, and business teams, to ensure the successful delivery of use cases. In this role, you will need to have a solid understanding of data warehouse design, relational databases such as PostgreSQL, Snowflake, SQL Server, as well as data lakehouse architectures. Your familiarity with cloud services for data and AI, such as Azure, AWS, or GCP, will be essential for ensuring data pipeline monitoring, cost optimization, and scalability in cloud environments. Furthermore, your exposure to Generative AI, RAG, embedding models, and vector databases like FAISS, Pinecone, ChromaDB, as well as experience with Agentic AI frameworks such as LangChain, Haystack, CrewAI, will be beneficial. Your knowledge of MLflow, Delta Live Tables, or other Databricks-native AI tools, CI/CD, Git, Docker, and DevOps pipelines will also be advantageous in this role. If you have a background in consulting, enterprise analytics, or AI/ML product development, it will further enhance your ability to excel in this position. Your excellent problem-solving and collaboration skills, coupled with your ability to bridge engineering and business needs, will be key to your success as a Senior Data Engineer + AI.,

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.,

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology. We are looking for an experienced AI Developer with proficiency in Python, Generative AI (GenAI) incorporating Retrieval-Augmented Generation (RAG), Robotic Process Automation (RPA), and advanced document intelligence utilizing OCR and LLMs. In this role, you will be responsible for developing AI-driven solutions that extract valuable insights from intricate documents, whether digital or scanned, by utilizing tools such as Tesseract, Hugging Face Transformers, or similar technologies. Your primary focus will be on creating end-to-end automation and AI integration for intelligent document processing, enhancing decision-making capabilities and optimizing workflow efficiencies throughout the organization. Key Responsibilities: - Develop and implement GenAI solutions with RAG pipelines to facilitate intelligent querying and summarization of document repositories. - Extract and organize data from complex documents (e.g., PDFs, Images) using a combination of OCR engines (e.g., Tesseract) and AI-based document and vision language models (DiNO, SmolVLM, etc.). - Incorporate OCR+LLM pipelines into business applications for processing scanned forms, contracts, and other unstructured documents. - Automate repetitive, document-centric tasks using RPA tools (e.g., Blue Prism, etc.). - Design and manage Python-based workflows to coordinate document ingestion, extraction, and LLM-powered processing. - Collaborate across various teams including product, data, and operations to deliver scalable, AI-enhanced document automation solutions. - Ensure model performance, compliance, and audit readiness for all document-handling workflows. Required Qualifications: - Minimum of 4 years of hands-on programming experience with Python. - Demonstrated expertise in building RAG-based GenAI applications using tools like LangChain, LlamaIndex, or equivalent. - Proficiency in OCR tools (e.g., Tesseract, PaddleOCR) and transformer-based document models. - Experience working with LLMs for document understanding, summarization, and Q&A. - Proficient in RPA development utilizing platforms like Blueprism, etc. - Knowledge of vector databases (e.g., FAISS, Pinecone) and embeddings for semantic retrieval. - Strong understanding of REST APIs, JSON, and data integration workflows. Please note that unless explicitly requested or approached by SS&C Technologies, Inc. or any of its affiliated companies, the company will not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services.,