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Role - AI Engineer : Typescript and Python, Gen AI, Agentic AI

Experience Required - 6+ Years

Role Overview: Design, develop, and deploy scalable AI/ML and GenAI solutions to solve complex business problems. Work closely with data scientists, business stakeholders, and cloud teams to build production-grade AI systems.

Must Have Technical/Functional Skills

6+ years of experience building large-scale distributed systems + strong experience with LLM systems, agentic workflows or advanced ML infrastructure, async processing, queues, and streaming systems
Experience working on Typescript and Python, Gen AI, Agentic AI
Advanced proficiency in Python, Hands-on experience with PyTorch, TensorFlow, Hugging Face.
Practical knowledge of model orchestration frameworks (e.g., LangChain, LlamaIndex, CrewAI), Familiarity with vector databases
Experience with cloud platforms (AWS, Azure AI, Google Cloud Vertex AI) and containerization technologies
Proven ownership of complex, cross-cutting agentic systems spanning multiple teams or products.
Strong engineering fundamentals across backend systems, APIs, data pipelines, and cloud infrastructure.
Deep experience across the agentic AI stack, including planning, tool use, memory, and evaluation.
Fluency with AI-assisted and agentic development workflows.
Ability to influence technical direction and align teams without formal authority.
Problem-solving, cross-functional collaboration, and the ability to articulate complex AI concepts to non-technical business stakeholders

Roles & Responsibilities

Drive technical direction for agentic AI initiatives, influencing architecture patterns, autonomy boundaries, and system design.
Design, build, and operate production-grade agentic AI systems used across multiple products.
Own and evolve shared agentic AI capabilities, including:
Design and Develop Agent frameworks and orchestration layers
Planning, tool use, and memory strategies
Design Retrieval and grounding (RAG) pipelines
LLM infrastructure, inference, and model gateways
Evaluation, observability, and safety tooling for autonomous systems
Lead technical design reviews and help teams navigate tradeoffs involving autonomy, safety, reliability, scalability, and cost.
Partner across teams to deliver complex, cross-cutting agentic AI initiatives from concept to production.
Evaluate emerging models, techniques, and agentic patterns and translate them into practical, enterprise-ready improvements.