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.
- Strong 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 fast-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