Agentic AI and Gen AI Engineer

About the Role:

We are looking for an ideal candidate with 5+ years of experience in Data Science / Machine Learning, with strong hands-on experience in Generative AI, Large Language Models (LLMs), NLP, and AI-powered applications. The candidate should be comfortable working across the complete AI lifecycle—from understanding business requirements and experimenting with models to building, evaluating, deploying, and monitoring production-grade GenAI solutions.

The role requires a combination of strong technical expertise, business understanding, problem-solving ability, and stakeholder management skills.

Key Responsibilities:

Generative AI & LLM

·      Design, develop, and deploy Generative AI and LLM-based solutions for enterprise use cases.

·      Work with models such as OpenAI, Azure OpenAI, Llama, Mistral, Gemini, or equivalent LLM platforms.

·      Develop applications using prompt engineering, structured outputs, function/tool calling, and LLM orchestration.

·      Design and implement Retrieval-Augmented Generation (RAG) solutions.

·      Work with vector databases and semantic search for enterprise knowledge retrieval.

·      Develop and evaluate AI agents and multi-step AI workflows.

·      Implement techniques such as prompt optimization, context management, grounding, and hallucination reduction.

·      Develop AI solutions for text classification, summarization, information extraction, question answering, document intelligence, and other enterprise use cases.

Machine Learning & Data Science

·      Develop and optimize traditional Machine Learning and statistical models where appropriate.

·      Perform data exploration, feature engineering, model selection, training, validation, and evaluation.

·      Apply appropriate ML and statistical techniques to solve business problems.

·      Work with structured, unstructured, and semi-structured data.

·      Develop scalable data pipelines to support AI/ML solutions.

·      Collaborate with Data Engineers to prepare and manage data for AI applications.

AI Evaluation & Productionization

·      Design evaluation frameworks to measure LLM accuracy, relevance, groundedness, toxicity, latency, and cost.

·      Implement guardrails and responsible AI practices.

·      Monitor model and application performance in production.

·      Identify model/data drift and implement appropriate improvement strategies.

·      Optimize AI solutions for performance, scalability, reliability, and cost.

·      Support deployment and productionization of AI/ML solutions.

·      Client & Delivery Responsibilities

·      Work closely with the CEO, Delivery team, Solution Architects, Engineering teams, and clients to understand business problems and identify AI opportunities.

·      Translate business requirements into practical AI/ML solutions.

·      Participate in client discussions, solution presentations, technical workshops, and POCs.

·      Develop rapid prototypes and demonstrate the feasibility of GenAI solutions.

·      Convert successful POCs into scalable, production-ready applications.

·      Provide technical guidance and contribute to AI solution architecture.

·      Prepare technical documentation, solution approaches, and project estimates where required.

·      Stay current with developments in Generative AI, LLMs, Agentic AI, and AI engineering.

Required Skills:

·       5+ years of hands-on experience in Data Science, Machine Learning, AI, or a related field.

·      Strong practical experience in Generative AI and LLM-based applications.

·      Strong proficiency in Python.

·      Strong understanding of Machine Learning and statistical concepts.

·      Hands-on experience with:

o       LLMs

o       Prompt Engineering

o       RAG

o       Vector Databases

o       Embeddings

o       Semantic Search

o       LLM Evaluation

o       AI Guardrails

·      Experience with frameworks/tools such as LangChain, LangGraph, LlamaIndex, or equivalent.

·      Experience with APIs and integrating LLMs into enterprise applications.

·      Strong SQL and data handling skills.

·      Experience working with large and complex datasets.

·      Strong understanding of NLP concepts.XX

Technical Skills:

·      Experience with OpenAI / Azure OpenAI / AWS Bedrock / Google Vertex AI.

·      Experience with vector databases such as Pinecone, Weaviate, Milvus, FAISS, or equivalent.

·      Experience with Databricks, Snowflake, or cloud data platforms.

·      Experience with Docker and CI/CD.

·      Exposure to AWS, Azure, or GCP.

·      Experience with ML/AI deployment and MLOps.

·       Knowledge of AI security, data privacy, governance, and responsible AI.

·      Experience building AI Agents / Agentic AI workflows.

·      Experience with multimodal AI is an added advantage

Key Competencies

·      Strong analytical and problem-solving ability.

·      Ability to translate business problems into practical AI solutions.

·      Strong communication and presentation skills.

·      Ability to interact confidently with senior stakeholders and clients.

·      Strong ownership and delivery mindset.

·      Ability to work independently in a fast-paced environment.

• Strong experimentation and innovation mindset.
• Ability to balance technical feasibility, business value, scalability, and cost.

Required Education & Experience:

·      Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related discipline