Key Responsibilities

Architect and scale AI-enabled search* systems for high-relevance semantic discovery across our product pipelines.

Build chat-based data insight* tools that allow users to query complex datasets via natural language.

Prototype and deploy Agentic AI* workflows to automate multi-step user workflows.

Implement strict AI Guardrails* to enforce safety, content policy, prompt injection defense, and structured data outputs.

Establish continuous LLM Evaluation* pipelines to benchmark accuracy, hallucination rates, and RAG retrieval performance.

Drive Model Optimization* techniques (caching, quantization, model selection, and prompt optimization) to minimize API latency and inference costs.
Collaborate closely with our core engineering team to ship production-ready APIs and microservices.

Qualifications
2–4 years of software engineering experience focusing on Machine Learning, NLP,



or LLM application engineering.

Robust proficiency in Python and TypeScript*.
Production backend framework experience in both ecosystems (e.g., FastAPI, Flask, Node.js, Express, or NestJS).
Hands-on experience with LLM orchestration (LangChain, LlamaIndex) and vector databases (Pinecone, Qdrant, Milvus, or Pgvector).
Familiarity with guardrail frameworks (e.g., NeMo Guardrails, Guardrails AI, or Llama Guard) and evaluation suites (e.g., Ragas, TruLens, DeepEval).
Demonstrated ability to optimize inference pipelines for cost, memory footprint, and speed.
Startup mindset: comfortable context-switching across 4 distinct products in a quick-paced setting.

Pay: ₹600,000.00 - ₹1,000,000.00 per year

Work Location: In person

📌 Mid Level Ai Engineer Full Stack Vadavalli
🏢 Techxlns
📍 Vadavalli