103 Rag Pipelines Jobs - Page 4

We are seeking an experienced and forward-thinking Generative AI Architect with a background of 12-15 years in AI/ML, with a specific focus on working with LLMs (Large Language Models) and Generative AI solutions. This pivotal role involves designing and supervising the development of cutting-edge GenAI platforms and solutions that revolutionize business operations and enhance customer experiences. As the GenAI Architect, you will collaborate closely with Data Scientists, ML Engineers, Product Teams, and Stakeholders to envision, prototype, and scale Generative AI Use Cases throughout the organization or for clients. Key responsibilities include leading the design and implementation of scalable GenAI solutions utilizing LLMs, diffusion models, and multimodal architectures. You will also be tasked with architecting end-to-end pipelines that encompass prompt engineering, vector databases, retrieval-augmented generation (RAG), and LLM fine-tuning. Furthermore, you will play a crucial role in selecting and integrating foundational models based on business requirements and technical limitations, defining GenAI architecture blueprints and best practices, and guiding teams on model evaluation, inference optimization, and cost-effective scaling strategies. Additionally, staying abreast of the rapidly evolving GenAI landscape, evaluating emerging tools, APIs, and frameworks, and collaborating with various stakeholders to identify high-impact GenAI use cases are essential aspects of this role. Requirements: - A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field. A PhD would be advantageous. - 12-15 years of experience in AI/ML and software engineering, with at least 3 years of dedicated focus on Generative AI and LLM-based architectures. Core Skills: - Profound expertise in machine learning, natural language processing (NLP), and deep learning architectures. - Hands-on familiarity with LLMs, transformers, fine-tuning techniques, and prompt engineering. - Proficiency in Python, including working knowledge of libraries/frameworks like Hugging Face Transformers, LangChain, OpenAI API, PyTorch, and TensorFlow. - Experience with vector databases and RAG pipelines. - Strong grasp of cloud-native AI architectures, containerization, and API integration. Architectural & Leadership Skills: - Demonstrated ability to design and implement scalable, secure, and efficient GenAI systems. - Excellent communication skills for effective cross-functional collaboration and stakeholder engagement. - Capacity to mentor engineering teams and foster innovation within the AI/ML ecosystem. Nice-to-Have: - Previous experience with multimodal models. - Understanding of AI governance, ethical AI, and compliance frameworks. - Familiarity with MLOps practices for GenAI, encompassing model versioning, drift detection, and performance monitoring.,

As a Technical Product Manager (TPM) at our company, you will play a crucial role in owning the end-to-end lifecycle of our AI platform and applications. Your responsibilities will include managing the product roadmap for AI-enabled applications, collaborating with engineering leads and designers, and ensuring the successful delivery of products aligned with business and technical goals. You will lead agile ceremonies such as sprint planning, backlog grooming, reviews, and retrospectives. Additionally, you will prioritize the product backlog based on value, effort, and technical feasibility, working closely with developers utilizing technologies like Python, React.js/Node.js, Vector DBs, and RDBMS. Furthermore, you will drive user research, collaborate with UI/UX teams to deliver high-impact interfaces, and partner with QA and DevOps to ensure smooth releases and performance tracking. Engaging with internal stakeholders and customers to capture feedback, validate features, and drive iteration will also be a key aspect of your role. To be successful in this position, you should hold a Bachelor's or Master's degree in Engineering, Computer Science, or a related field, along with 6+ years of overall experience, including 3+ years in a Technical Product Manager or Agile Product Owner role. Your solid understanding of modern technology stacks and proficiency in product management tools will be essential. Preferred qualifications include exposure to AI/ML-based products, familiarity with DevOps practices and API testing tools, as well as certification in Scrum, SAFe, or Agile Product Management. Experience in B2B SaaS product development will also be advantageous. Join us to work at the cutting edge of AI, UX, and scalable architecture, taking ownership of mission-critical products that are reshaping enterprise automation. You will have the opportunity to collaborate with a talented cross-functional team in a dynamic, innovation-driven culture, offering competitive salary, flexible working options, and growth opportunities.,

DecisionX is pioneering a new category with the world's first Decision AI, an AI Super-Agent that assists high-growth teams in making smarter, faster decisions by transforming fragmented data into clear next steps. Whether it involves strategic decisions in the boardroom or operational decisions across various departments like Sales, Marketing, Product, and Engineering, down to the minutiae that drives daily operations, Decision AI serves as your invisible co-pilot, thinking alongside you, acting ahead of you, and evolving beyond you. We are seeking a dedicated and hands-on AI Engineer to join our Founding team. In this role, you will collaborate closely with leading AI experts to develop the intelligence layer of our exclusive "Agentic Number System." Key Responsibilities - Building, fine-tuning, and deploying AI/ML models for tasks such as segmentation, scoring, recommendation, and orchestration. - Developing and optimizing agent workflows using LLMs (OpenAI, Claude, Mistral, etc.) for contextual reasoning and task execution. - Creating vector-based memory systems utilizing tools like FAISS, Chroma, or Weaviate. - Working with APIs and connectors to incorporate third-party data sources (e.g., Salesforce, HubSpot, GSuite, Snowflake). - Designing pipelines that transform structured and unstructured signals into actionable insights. - Collaborating with GTM and product teams to define practical AI agent use cases. - Staying informed about the latest developments in LLMs, retrieval-augmented generation (RAG), and agent orchestration frameworks (e.g., CrewAI, AutoGen, LangGraph). Must Have Skills - 5-8 years of experience in AI/ML engineering or applied data science. - Proficient programming skills in Python, with expertise in LangChain, Pandas, NumPy, and Scikit-learn. - Experience with LLMs (OpenAI, Anthropic, etc.), prompt engineering, and RAG pipelines. - Familiarity with vector stores, embeddings, and semantic search. - Expertise in data wrangling, feature engineering, and model deployment. - Knowledge of MLOps tools such as MLflow, Weights & Biases, or equivalent. What you will get - Opportunity to shape the AI architecture of a high-ambition startup. - Close collaboration with a visionary founder and experienced product team. - Ownership, autonomy, and the thrill of building something from 0 to 1. - Early team equity and a fast growth trajectory.,

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.,

Wipro Limited is a leading technology services and consulting company that focuses on creating innovative solutions to meet the complex digital transformation needs of clients. With a vast portfolio of capabilities in consulting, design, engineering, and operations, Wipro helps clients achieve their bold ambitions and build sustainable businesses. The company, with over 230,000 employees and business partners in 65 countries, is committed to assisting customers, colleagues, and communities in thriving in a rapidly evolving world. To learn more, visit www.wipro.com. Role: Data Science GenAI Architect Title: Data Science Architect Location: Gurgaon / Noida Key Responsibilities: - Develop working proof of concepts (POC) and prototypes quickly. - Create and integrate AI-driven solutions to address identified opportunities and challenges. - Lead cross-functional teams to identify and prioritize key business areas where AI solutions can deliver benefits. - Present proposals to executives and business leaders on various technology strategies, standards, and governance for AI. - Collaborate with engineering and business leaders on functional design, process design, prototyping, testing, and defining support models. - Document and articulate solutions architecture and lessons learned from each exploration and accelerated incubation. Relevant IT Experience: - Minimum of 10 years of relevant IT experience in the specified technology. Competencies: - Client Centricity - Passion for Results - Execution Excellence - Problem Solving & Decision Making - Effective Communication Mandatory Skills: Technology (Alight IT) Experience: 8-10 Years At Wipro, we are shaping a modern organization focused on end-to-end digital transformation. We are seeking individuals who are inspired by reinvention - of themselves, their careers, and their skills. Join us in our journey to constantly evolve our business and industry. At Wipro, we embrace change and empower you to design your own reinvention. Realize your ambitions with us. We welcome applications from individuals with disabilities.,

We are looking for Senior Software Engineer (AI/ML NLP & Generative AI) , You'll make an impact by Design, develop, and optimize NLP-driven AI solutions using state-of-the-art models and techniques (NER, embeddings, summarization, etc.). Build and productionize RAG pipelines and agentic workflows to support intelligent, context aware applications. Fine-tune, prompt-engineer, and deploy LLMs (OpenAI, Anthropic, Falcon, LLaMA, etc.) for domain-specific use cases. Collaborate with data scientists, backend developers, and cloud architects to build scalable AI first systems. Evaluate and integrate third-party models/APIs and open-source libraries for generative use cases. Continuously monitor and improve model performance, latency, and accuracy in production settings. Implement observability, performance monitoring, and explainability features in deployed models. Ensure solutions meet enterprise-level requirements for reliability, traceability, and maintainability. Use your skills to move the world forward! Master's or Bachelor's degree in Computer Science, Machine Learning, AI, or a related field. 5+ years of overall experience in AI/ML, with at least 2+ years in NLP and 1'2 years in Generative AI. Strong understanding of LLM architectures, fine-tuning methods (LoRA, PEFT), embeddings, and vector search. Experience in designing and deploying RAG pipelines and working with multi-step agent architectures. Proficiency in Python and frameworks like Lang Chain, Transformers (Hugging Face), Llama Index, Smol Agents, etc. Familiarity with ML observability and explainability tools (e.g., Tru Era, Arize, Why Labs). Knowledge of cloud-based ML services like AWS Sagemaker, AWS Bedrock, Azure OpenAI Service, Azure ML Studio, and Azure AI Foundry. Experience in integrating LLM-based agents in production environments. Understanding of real-time NLP challenges (streaming, latency optimization, multi-turn dialogues). Familiarity with Lang Graph, function calling, and tools for orchestration in agent-based systems. Exposure to infrastructure-as-code (Terraform/CDK) and DevOps for AI pipelines. Domain knowledge in Electrification, Energy, or Industrial AI is a strong plus.

We are looking for a highly motivated Mid-Level AI Engineer to join our growing AI team. Your main responsibility will be to develop intelligent applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. Working closely with data scientists, backend engineers, and product teams, you will build and deploy AI-powered solutions that provide real-world value. Your key responsibilities will include designing, developing, and optimizing applications utilizing LLMs such as GPT, LLaMA, and Claude. You will also be tasked with implementing RAG pipelines to improve LLM performance using domain-specific knowledge bases and search tools. Developing and maintaining robust Python codebases for AI-driven solutions will be a crucial part of your role. Additionally, integrating vector databases like Pinecone, Weaviate, and FAISS, as well as embedding models for information retrieval, will be part of your daily tasks. You will work with APIs, frameworks like LangChain and Haystack, and various tools to create scalable AI workflows. Collaboration with product and design teams to define AI use cases and deliver impactful features will also be a significant aspect of your job. Conducting experiments to assess model performance, retrieval relevance, and system latency will be essential for continuous improvement. Staying up-to-date with the latest research and advancements in LLMs, RAG, and AI infrastructure is crucial for this role. To be successful in this position, you should have at least 3-5 years of experience in software engineering or AI/ML engineering, with a strong proficiency in Python. Experience working with LLMs such as OpenAI and Hugging Face Transformers is required, along with hands-on experience in RAG architecture and vector-based retrieval techniques. Familiarity with embedding models like SentenceTransformers and OpenAI embeddings is also necessary. Knowledge of API design, deployment, performance optimization, version control (e.g., Git), containerization (e.g., Docker), and cloud platforms (e.g., AWS, GCP, Azure) is expected. Preferred qualifications include experience with LangChain, Haystack, or similar LLM orchestration frameworks. Understanding NLP evaluation metrics, prompt engineering best practices, knowledge graphs, semantic search, and document parsing pipelines will be beneficial. Experience deploying models in production, monitoring system performance, and contributing to open-source AI/ML projects are considered advantageous for this role.,

You are a Data Science Engineer who will be contributing to the development of intelligent, autonomous AI systems. The ideal candidate should have a strong background in agentic AI, LLMs, SLMs, vector DB, and knowledge graphs. Your responsibilities will include deploying AI solutions that leverage technologies such as Retrieval-Augmented Generation (RAG), multi-agent frameworks, and hybrid search techniques to enhance enterprise applications. As part of the flexible scheme, you will enjoy various benefits such as a best-in-class leave policy, gender-neutral parental leaves, childcare assistance benefit reimbursement, sponsorship for industry-relevant certifications, employee assistance program, comprehensive hospitalization insurance, accident and term life insurance, and health screening. Your key responsibilities will involve designing and developing Agentic AI Applications using frameworks like LangChain, CrewAI, and AutoGen, implementing RAG Pipelines, fine-tuning Language Models, training NER Models, developing Knowledge Graphs, collaborating cross-functionally, and optimizing AI workflows. To excel in this role, you should have at least 4 years of professional experience in AI/ML development, proficiency in Python, Python API frameworks, SQL, and familiarity with AI/ML frameworks like TensorFlow or PyTorch. Experience in deploying AI models on cloud platforms, understanding of LLMs, SLMs, semantic technologies, and MLOps tools is required. Additionally, hands-on experience with vector databases, embedding techniques, and developing AI solutions for specific industries will be beneficial. You will receive support through training, coaching, and a culture of continuous learning to aid in your career progression. The company strives for a culture of empowerment, responsibility, commercial thinking, initiative, and collaboration. They promote a positive, fair, and inclusive work environment for all individuals. For further information about the company and its teams, please visit the company website at https://www.db.com/company/company.htm. Join a team that celebrates success and fosters a culture of excellence and inclusivity.,

You are looking for a visionary Data Science Manager with expertise in Generative AI and Retrieval-Augmented Generation (RAG) to lead AI initiatives from both technical and business perspectives. In this role, you will lead a team of data scientists and ML engineers, design Generative AI models, develop statistical models, and integrate knowledge retrieval systems to enhance performance. Your responsibilities will include mentoring the team, designing scalable AI/ML solutions, implementing Generative AI models, and developing statistical models for forecasting and segmentation. You will also be responsible for integrating databases and retrieval systems, ensuring operational excellence in MLOps, and collaborating with various teams to identify high-impact use cases for GenAI. To qualify for this role, you should have a Masters in Computer Science or related fields, 10+ years of data science experience with 2+ years in GenAI initiatives, proficiency in Python and key libraries, and a strong foundation in statistical analysis and predictive modeling. Experience in cloud platforms, vector databases, and MLOps is essential, along with a background in sectors like legal tech, fintech, retail, or health tech. If you have a proven track record in building and deploying LLMs, RAG systems, and search solutions, along with a knack for influencing product roadmaps and executive strategy, this role is perfect for you. Your ability to translate complex AI concepts into actionable strategies and present findings to non-technical audiences will be crucial in driving AI/ML adoption and contributing to the company's innovation roadmap.,

We are seeking a Mid-Level LLM Application Developer with 3+ years of experience in software development, who is enthusiastic about constructing intelligent applications utilizing Azure OpenAI, Python, and LLM frameworks. This full-time position is dedicated to the design, development, and implementation of scalable LLM-powered solutions, such as chatbots, knowledge assistants, and RAG-based systems. You will collaborate closely with cross-functional teams to materialize innovative AI solutions, capitalizing on the latest generative AI and agentic technologies. Responsibilities: - Design and develop LLM-powered applications utilizing Python and Azure OpenAI services. - Construct end-to-end Retrieval-Augmented Generation (RAG) pipelines, incorporating vector databases, semantic search, and related tools. - Develop conversational agents and virtual assistants, employing frameworks like LangChain or LlamaIndex. - Create effective prompts using advanced prompt engineering and design techniques. - Integrate LLMs with external tools, APIs, and business data systems. - Apply Agentic AI patterns to RAG and AI Workflows, engaging with LLMs by orchestrating various agents together. - Deploy and manage applications using Azure Functions, Azure AI services, and serverless components. - Ensure performance, scalability, and reliability of AI solutions on Azure. - Collaborate across teams and participate in agile development processes. Required Skills (Must Have): - Proficiency in Python programming language. - Expertise in Azure OpenAI Service, including foundation model usage and integration. - Build and deploy AI solutions leveraging Azure AI services (e.g., Cognitive Services, Azure ML, Azure AI Search). - Deep experience in prompt engineering, including various prompting strategies (few-shot, chain-of-thought, etc.). - Hands-on experience building RAG pipelines with vector databases and tool integrations. - Proven experience developing chatbots or virtual assistants using LLMs. - Proficiency in at least one LLM application framework (e.g., LangChain, LlamaIndex). - In-depth understanding of LLM models, their capabilities, and applications. - Good understanding of LLM evaluations, and how to evaluate LLM model outputs. - Good understanding of using AI Agents and Agentic AI Patterns to integrate with LLMs. - Experience deploying with Azure Function Apps and broader Azure ecosystem. - Solid grasp of API integrations and data workflow design. - Strong problem-solving skills and ability to deliver scalable, efficient code. - Excellent communication and team collaboration abilities. Preferred Skills (Good to Have): - Familiarity with Multi-Agent AI orchestration and agentic workflows. - Experience building cloud-native services with serverless architectures. - Understanding of NLP techniques and data transformation pipelines. - Familiarity with LLMOps concepts and AI model lifecycle. Qualifications: - Bachelor's degree in computer science, Computer Engineering, or a related field. - 3+ years of experience in software development. - Experience with LLM applications and cloud platforms. - Strong understanding of software development methodologies (e.g., Agile). Location: DGS India - Pune - Kharadi EON Free Zone Brand: Dentsu Creative Time Type: Full time Contract Type: Permanent,

What You ll Do Design & Build: Develop mutli-agent AI systems for the UCaaS platform, focusing on NLP, speech recognition, audio intelligence and LLM powered interactions. Rapid Experiments: Prototype with open-weight models (Mistral, LLaMA, Whisper, etc.) and scale what works. Code for Excellence: Write robust code for AI/ML libraries and champion software best practices. Optimize for Scale & Cost: Engineer scalable AI pipelines, focusing on latency, throughput, and cloud costs. Innovate with LLMs: Fine-tune and deploy LLMs for summarization, sentiment and intent detection, RAG pipelines, multi-modal inputs and multi-agentic task automation. Own the Stack: Lead multi-agentic environments from data to deployment and scale. Collaborate & Lead: Integrate AI with cross-functional teams and mentor junior engineers. What You Bring Experience:6-10 yearsof professional experience, with a mandatory minimum of 2 years dedicated to a hands-on role in a real-world, production-level AI/ML project. Coding & Design: Expert-level programming skills inPythonand proficiency in designing and building scalable, distributed systems. ML/AI Expertise: Deep, hands-on experience with coreML/AI libraries and frameworks, Agentic Systems, RAG pipelines Hands-on experience in usingVector DBs LLM Proficiency: Proven experience working with and fine-tuning Large Language Models (LLMs). Scalability & Optimization Mindset: Demonstrated experience in building and scaling AI services in the cloud, with a strong focus on performance tuning and cost optimization of agents specifically. Nice to Have Youve tried outagent frameworkslike LangGraph, CrewAI, or AutoGen and can explain the pros and cons of autonomous vs. orchestrated agents. Experience with MLOps tools and platforms (e.g., Kubeflow, MLflow, Sagemaker). Real-time streaming AI experience token-level generation, WebRTC integration, or live transcription systems Contributions to open-source AI/ML projects or a strong public portfolio (GitHub, Kaggle).

We're hiring a passionate Data Scientist / GenAI Engineer to join our AI-first team working on LLMs, RAG pipelines, NLP features, and GenAI use cases like chatbots, recommendation engines, and smart automation.

Design, build, and productionize GenAI-powered tools and featuresusing APIs like OpenAI, Claude, etc. Help shape ourarchitecture, prompt engineering strategies, and evaluation frameworks Guide the team on when to use RAG vs. fine-tuning vs. function calling, etc. Prototype quickly, validate ideas, and help turn the best ones into durable solutions Use TDD (Test Driven Development) to ship code that is maintainable and which stay bug free Work closely with product, engineering, and data stakeholders to ship real value Mentor junior engineers, review code, and lead by example technical guidance, not bureaucracy Stay on top of GenAI trends, tools, benchmarks, and bring clarity on what s real vs. hype Responsibilities Have 6-8+ years of engineering experience, ideally across multiple companies or industries Haveshipped GenAI-powered featuresinto production (not just toy projects) Have strongprogramming and problem-solving skills Are fluent inPythonand comfortable integrating APIs, building backends, or working with embeddings Have strongproduct thinkingyou care about solving user problems, not just building cool tech Can communicate clearly across disciplines from junior devs to product managers Are comfortable working inambiguous, fast-moving environments Youve used dev tools like Cursor, Replit, or other AI coding assistants Have a learning mindset and are excited to work with folks earlier in their GenAI journey Good to have Experience withLangChain, LlamaIndex, RAG pipelines, or similar Familiar withprompt engineering,model evaluation, orLLM observability Have experimented withfunction calling, agents, or tool use Have experience withinternal tool development, scripting, or automation Active side projects, blog posts, or OSS contributions in GenAI

Role & responsibilities Machine Learning, Data Science, Model Customization [4+ Years] Exp with performing above on cloud services e.g AWS SageMaker and other tools AI/ Gen AI skills: [1 or 2 years] MCP, RAG pipelines, A2A, Agentic / AI Agents Framework Auto Gen, Lang graph, Lang chain, codeless workflow builders etc. Preferred candidate profile Build working POC and prototypes rapidly. Build / integrate AI driven solutions to solve the identified opportunities, challenges. Lead cross functional teams in identifying and prioritizing key business areas in which AI solutions can result benefits. Proposals to executives and business leaders on broad range of technology, strategy and standard, governance for AI. Work on functional design, process design (flow mapping), prototyping, testing, defining support model in collaboration with Engineering and business leaders. Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation. Relevant IT Experience: - 10+ years of relevant IT experience in given technology

1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. What you will bring to the Table: Technical Skills 8+ Years of overall experience, Strong expertise in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Job Title: Executive AI Engineering Location: Andheri (Mumbai) Industry: Pharmaceutical Experience Required: 4+ years in Gen AI/ML, NLP application development About the Role: We are looking for a highly skilled Senior AI Engineer GenAI & Applied ML to independently design, develop, and deploy advanced AI solutions. This is a senior individual contributor role focused on building production-grade Generative AI systems, agentic applications, and intelligent bots using state-of-the-art LLMs, SLMs, and embedding models. You’ll work hands-on across the full AI stack — from fine-tuning models and writing APIs to implementing text-to-SQL and voice-enabled assistants. If you have a strong track record of single-handedly delivering complex AI systems and a deep understanding of modern ML and GenAI trends. Key Responsibilities: Design, build, and deploy production-ready AI solutions leveraging LLMs, SLMs, embedding models, and advanced ML techniques. Develop intelligent chat agents, voice-enabled bots, and autonomous agentic AI systems tailored to various domains and user contexts. Implement context-aware systems using RAG (Retrieval-Augmented Generation), custom embeddings, and vector databases to optimize relevance and response quality. Fine-tune and customize open-source and proprietary LLMs (e.g., GPT, Claude, LLaMA, Mistral, Phi 4) for domain-specific applications and enhanced performance. Build and expose scalable APIs to serve AI models and integrate them into broader application ecosystems. Own the full AI lifecycle — from architecture and experimentation to deployment and performance tuning. Translate business needs into technical blueprints in collaboration with product owners, data teams, and domain experts. Proactively research and prototype with the latest advancements in GenAI, agent frameworks, and multimodal models to drive innovation. Understanding of evaluation frameworks for GenAI systems, including prompt robustness, hallucination mitigation, and human-in-the-loop feedback loops. Requirements: 4 + years of hands-on experience in building and deploying AI/ML/NLP applications, including at least 2 years working with LLMs or GenAI systems in production environments. Proven experience with state-of-the-art LLMs/SLMs , such as GPT-3.5/4, Claude, LLaMA, Mistral, or similar, including prompt engineering, model evaluation, and fine-tuning. Practical expertise in building RAG pipelines , designing embedding workflows , and using vector databases like FAISS, Pinecone, or Weaviate. Strong Python programming skills with experience in Hugging Face Transformers , LangChain , LanGraph, OpenAI/Anthropic SDKs , and other GenAI frameworks. Solid grasp of ML/NLP fundamentals including data preprocessing , model optimization , evaluation metrics , and real-world deployment strategies . Familiarity with deploying AI models through APIs, cloud platforms, or containerized environments (e.g., Docker, FastAPI, Flask). Excellent analytical and debugging skills; ability to independently research, prototype, and solve complex problems end-to-end. Bonus: Exposure to voice AI systems , speech-to-text APIs, or audio-driven interfaces is an advantage. Nice to Have: Familiarity with regulatory and compliance frameworks relevant to AI in life sciences, such as GxP , HIPAA , GDPR , or similar standards. Experience integrating AI models into enterprise platforms , pharma-specific systems , or regulated IT environments . Knowledge of agent frameworks (e.g., AutoGen, CrewAI, LangGraph) and how to operationalize them in real-world use cases. Exposure to speech recognition APIs , voice interface design, or building voice-enabled assistants . Educational Qualifications: Bachelor’s Degree in Engineering (B.E./ B.Tech. ) or Master’s Degree in Computer Applications (MCA/ M.Tech) . Additional Qualifications in Artificial Intelligence, Machine Learning, or Data Science are highly desirable. Benefits We Offer: Access to a state-of-the-art facility equipped with modern and collaborative workspaces. Free gym facility to promote health and well-being of employees. Dynamic and inclusive work environment focused on innovation and continuous learning. Opportunity to work on impactful projects at the intersection of AI and life sciences. Competitive compensation.

Key Deliverables: Build and maintain scalable data pipelines for structured and unstructured data Implement ETL/ELT processes and integrate with GenAI systems Develop solutions using cloud platforms and big data technologies Collaborate with cross-functional teams to support data governance and AI initiatives Role Responsibilities: Design and develop high-performance data solutions for GenAI use cases Translate business needs into technical architecture and data workflows Ensure data quality, privacy, and security across systems Optimize data infrastructure and support continuous integration/deployment

* If you are 5+ years experienced and Immediate joiner , please apply: https://docs.google.com/forms/d/e/1FAIpQLScorR1zEgu9FvDHO-4gjJEOPhk_2tJE6cgftARiy9rwcVcDHg/viewform 5+ years of experience as a backend or full-stack engineer with a strong backend focus Advanced proficiency in Python Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar) Background in machine learning engineering is a strong plus Solid understanding of service architecture and production deployment workflows Hands-on LLM integration in production (not academic/chatbot-only experience) Expertise in designing production-grade APIs and backend services Strong knowledge of async workflows, deployment, observability, and performance *This is a software engineering role (not data science, analytics, or annotation)* Description: A complete remote role, you can use your own laptop. 8hrs/day, Mon-Fri required Eligibility: Candidates with 5+ years of relevant professional experience are eligible to apply.Must possess strong communication skills , both written and verbal.Should have proven expertise in the specific field or role being applied for. Interview Pattern: Screening Interview - 30 min on google meet Second Interview - 60 min Final Client Interview - 30 min Govt Id should be shown in all interviews and camera is a must. Timings: 8 hrs/day, Mon-Fri Salary will be competitive above the market standards and will be calculated on hourly basis. Role & responsibilities Preferred candidate profile : Immediate Joiners

Greetings of the Day !! We have job opening for UiPath Developer with one of our clients . if you are interested for this position please share update resume . Location : Bangalore/ Pune/Hyderabad/ Indore Job Title: Tech Lead Intelligent Automation (UiPath + LLM Integration) Job Summary We are looking for a Tech Lead with deep expertise in UiPath as the primary automation platform and a strong background in integrating Large Language Models (LLMs) to enhance intelligent automation capabilities. This role involves leading solution design, architecture, and implementation of enterprise-grade automation systems that combine RPA with AI/LLM features such as document understanding, translation, and conversational automation. As a Tech Lead, you will mentor teams, define best practices, and drive innovation using UiPath and LLM technologies across the automation landscape. Key Responsibilities Lead architecture, design, and delivery of UiPath automation solutions integrated with LLMs to solve complex business challenges. Work closely with stakeholders to identify automation opportunities and define technical strategies using UiPath, AI Center, Document Understanding, and LLM APIs. Drive the integration of LLMs (e.g., OpenAI, Azure OpenAI, Google Gemini) into UiPath workflows for intelligent tasks such as summarization, classification, translation, and Q&A. Define reusable frameworks, standards, and best practices for LLM-augmented UiPath solutions. Guide development teams in building scalable and secure automation solutions using orchestrator, REFramework, and custom components. Own code reviews, solution documentation, and ensure delivery meets performance, security, and quality benchmarks. Provide technical leadership, mentorship, and training to UiPath developers and LLM engineers. Stay ahead of automation and AI trends, and proactively propose innovations aligned with business goals. Required Skills & Qualifications Bachelors or Masters degree in Computer Science, Engineering, or related discipline. 7+ years of experience in automation , with at least 5 years of hands-on UiPath experience including enterprise-grade solution delivery. Strong experience with UiPath Orchestrator, AI Center, Document Understanding , and REFramework. Hands-on experience in integrating LLMs into UiPath workflows using REST APIs, Python components, or custom activities. Deep understanding of prompt engineering, chunking, embeddings, and LLM-based document processing strategies. Proficiency in Python and API integration for external AI/LLM systems. Solid understanding of cloud AI services (Azure AI, Vertex AI, AWS AI) and vector databases (FAISS, Pinecone, Weaviate). Excellent communication, stakeholder management, and team leadership skills. Proven experience in mentoring teams, driving automation strategy, and ensuring solution scalability and maintainability. Preferred Skills (Nice to Have) UiPath Solution Architect or Advanced RPA Developer certification . Experience with LangChain , RAG pipelines, and LLM deployment at scale. Exposure to Power Platform, Microsoft Copilot Studio, or similar AI-enhanced low-code environments. Familiarity with DevOps practices in automation environments (CI/CD, version control, etc.). Knowledge of enterprise security, compliance, and governance in RPA + AI solutions. Thanks, Shaswati

Job Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

Develop and deploy ML pipelines using MLOps tools, build FastAPI-based APIs, support LLMOps and real-time inferencing, collaborate with DS/DevOps teams, ensure performance and CI/CD compliance in AI infrastructure projects. Required Candidate profile Experienced Python developer with 4–8 years in MLOps, FastAPI, and AI/ML system deployment. Exposure to LLMOps, GenAI models, containerized environments, and strong collaboration across ML lifecycle

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Role & responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Preferred candidate profile Qualifications Must-Haves: 5+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcdeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

Interview mode: In-person( Varanasi) | Exp: 2-5 yrs Develop & maintain Python/Django backends, implement LangChain & RAG, build AI workflows, optimize data, manage MySQL, deploy via Docker/Linux; plus web scraping(BS4), Cloud, HTML/CSS is a bonus.

We're looking for an experienced AI/ML Technical Lead to architect and drive the development of our intelligent conversation engine. Youll lead model selection, integration, training workflows (RAG/fine-tuning), and scalable deployment of natural language and voice AI components. This is a foundational hire for a technically ambitious platform. Role & responsibilities AI System Architecture: Design the architecture of the AI-powered agent including LLM-based conversation workflows, voice bots, and follow-up orchestration. Model Integration & Prompt Engineering: Leverage APIs from OpenAI, Anthropic, or deploy open models (e.g., LLaMA 3, Mistral). Implement effective prompt strategies and retrieval-augmented generation (RAG) pipelines for contextual responses. Data Pipelines & Knowledge Management: Build secure data pipelines to ingest, embed, and serve tenant-specific knowledge bases (FAQs, scripts, product docs) using vector databases (e.g., Pinecone, Weaviate). Voice & Text Interfaces: Implement and optimize multimodal agents (text + voice) using ASR (e.g., Whisper), TTS (e.g., Polly), and NLP for automated qualification and call handling. Conversational Flow Orchestration: Design dynamic, stateful conversations that can take actions (e.g., book meetings, update CRM records) using tools like LangChain, Temporal, or n8n. Platform Scalability: Ensure models and agent workflows scale across tenants with strong data isolation, caching, and secure API access. Lead a Cross-Functional Team: Collaborate with backend, frontend, and DevOps engineers to ship intelligent, production-ready features. Monitoring & Feedback Loops: Define and monitor conversation analytics (drop-offs, booking rates, escalation triggers), and create pipelines to improve AI quality continuously. Preferred candidate profile Qualifications Must-Haves: 4+ years of experience in ML/AI, with at least 2 years leading conversational AI or LLM projects. Strong background in NLP, dialog systems, or voice AI preferably with production experience. Experience with OpenAI, or open-source LLMs (e.g. LLaMA, Mistral, Falcon) and orchestration tools (LangChain, etc.). Proficiency with Python and ML frameworks (Hugging Face, PyTorch, TensorFlow). Experience deploying RAG pipelines, vector DBs (e.g. Pinecone, Weaviate), and managing LLM-agent logic. Familiarity with voice processing (ASR, TTS, IVR design). Solid understanding of API-based integration and microservices. Deep care for data privacy, multi-tenancy security, and ethical AI practices. Nice-to-Haves: Experience with CRM ecosystems (e.g. Salesforce, HubSpot) and how AI agents sync actions to CRMs. Knowledge of sales pipelines and marketing automation tools. Exposure to calendar integrations (Google Calendar API, Microsoft Graph). Knowledge of Twilio APIs (SMS, Voice, WhatsApp) and channel orchestration logic. Familiarity with Docker, Kubernetes, CI/CD, and scalable cloud infrastructure (AWS/GCP/Azure). What We Offer Founding team role with strong ownership and autonomy Opportunity to shape the future of AI-powered sales Flexible work environment Competitive salary Access to cutting-edge AI tools and training resources Post your resume and any relevant project links (GitHub, blog, portfolio) to career@sourcdeskglobal.com. Include a short note on your most interesting AI project or voicebot/conversational AI experience.

Role & responsibilities Machine Learning, Data Science, Model Customization [4+ Years] Exp with performing above on cloud services e.g AWS SageMaker and other tools AI/ Gen AI skills: [1 or 2 years] MCP, RAG pipelines, A2A, Agentic / AI Agents Framework Auto Gen, Lang graph, Lang chain, codeless workflow builders etc. Preferred candidate profile Build working POC and prototypes rapidly. Build / integrate AI driven solutions to solve the identified opportunities, challenges. Lead cross functional teams in identifying and prioritizing key business areas in which AI solutions can result benefits. Proposals to executives and business leaders on broad range of technology, strategy and standard, governance for AI. Work on functional design, process design (flow mapping), prototyping, testing, defining support model in collaboration with Engineering and business leaders. Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation. Relevant IT Experience: - 10+ years of relevant IT experience in given technology