About this role
Need: 4-6 years & 6-8 years
Job Description:
We are looking for highly skilled Engineering Graduate as Lead AI / Generative AI to drive the end-to-end development and delivery of advanced AI solutions. The role involves designing scalable GenAI architecture, working with cross-functional teams, and building production-grade AI systems using modern open-source frameworks.
The ideal candidate will have strong expertise in LLMs, RAG pipelines, AI agents, and API-driven architecture, along with proven leadership experience in delivering AI projects from concept to production. He/she should drive end-to-end project delivery, build production-grade systems using LLMs, RAG pipelines, and AI agents, and mentor teams while aligning solutions with business needs.
Technical Qualifications (Essential)
Strong Python programming
Experience with FastAPI based API development
Knowledge of NLP frameworks & techniques
Hands-on with Vector Databases (Milvus/FAISS/Pinecone/Weaviate)
Expertise in LLMs, RAG, embeddings
Familiarity with Docker, Kubernetes
Basic understanding of cloud platforms - AWS / Azure / GCP
Primary Skills
Generative AI: RAG pipelines, embeddings, semantic search, LLM inference, fine-tuning.
Prompt Engineering: Context design, optimization techniques, advanced prompt engg techniques
AI Agentic Frameworks: LangChain, LangGraph, LangSmith
API Development: Scalable, AI-integrated services
Secondary Skills
Cloud deployment
MLOps / LLMOps practices
Performance & cost optimization
Data engineering fundamentals
Good to have - Statistical techniques such as Logistic Regression Multivariate Regression, Stochastic Processes, Decision Trees, common clustering algorithms, Optimization etc.,
Experience
4+ years years in AI/ML/GenAI
Delivered 2+ end-to-end AI/Gen AI projects
Built 5+ Agents/agent-based applications
Experience in creating AI/Gen AI project’s SoW, solution approach, estimation, and token management & costing
Functional & Technical Responsibilities
Design & develop AI/GenAI solutions (RAG, agents)
Develop & optimize prompts and LLM workflows
Build scalable APIs and backend systems
Lead end-to-end project delivery to production
Create solution proposals, SoW, architecture
Awareness of deployments (Docker/K8s)
Mentor teams & drive best practices
Translating business problems into AI solutions