Generative AI Engineer

AI Engineer (production / apps focus):
Design and ship AI-powered product features (LLMs, RAG, agents, ML APIs) into our
existing services, working closely with backend, frontend, and data science teams.
 Integrate off-the-shelf and inhouse models (LLMs, embeddings, ML APIs) into robust
microservices and user facing flows.
 Design and implement RAG and workflow/agent pipelines: retrieval, context
assembly, tools integration, guardrails, and fallbacks.
 Own AI service reliability in production: latency, throughput, cost,
observability, circuit breakers, and rollback/versioning of models and prompts.

 Collaborate with Data Scientists who own model training/fine tuning and evaluation
design; product ionize their outputs as stable APIs/workflows.
 Implement logging, feedback capture, and lightweight online evaluation hooks to
measure quality of AI features over time.
 Ensure safety, security, and compliance for AI features: prompt injection defenses, PII
handling, abuse/hallucination controls, and audit trail.
 Contribute to internal AI tooling: SDKs, templates, and reusable components to
accelerate future AI use case.

Skills required:

AI Engineer role demands more than AI-based augmentation with in-depth understanding of
concepts like
- -RAG
-GenAI, LLM fine tuning, Prompt engineering
-Multi-Agent framework (langchain, langraph etc with hands on experience)
-Eval generation and their importance
-Tokens usage and optimisations.
-Model/mcp gateway
Ideal profile:
 Strong software engineering in Python (and one of Node/Java/Go),
REST/gRPC APIs, queues, and microservices on cloud infra.
 Handson experience shipping at least one AI powered product to production (e.g.,
search, recommendations, chatbots, summarization, classification)
 Practical knowledge of LLM concepts: prompts, context engineering, embeddings,
vector search, basic evaluation metrics, and latency/cost trade-offs.
 Solid understanding of integration patterns with third party AI providers (OpenAI,
Anthropic, etc.) and vector DB
 Hand-on & good understanding of atleast one agentic framework like Langgraph.