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Lead Engineer

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Onsite

Lead Engineer

R Systems

Lead Engineer

Skills

DockerPythonAIAWSNLP / Natural Language Processing

6 days ago

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Important information


Contract type:

Permanent

Work mode:

Onsite

Published on:

15 October 2026

What they need


Urgent opening with R systems.

Required Qualifications

Job location: Bangalore (Mandatory)

Work from Office: Yes

Looking for Immediate joiner only.

Exp level: 6-9 Yrs

Interested candidates can share updated profile at [email protected]

Core Experience

  • 6+ years of software engineering experience , with 3+ years building and shipping LLM-powered applications in production.
  • Strong Python skills — production-quality code, clean architecture, type-safe data modeling (Pydantic or equivalent), and testable design.
  • Hands-on production experience with at least one major LLM provider — AWS Bedrock, Anthropic Claude, OpenAI GPT, Google Gemini, or equivalent — including tool/function calling and structured output.
  • Demonstrated experience building RAG systems end to end — chunking, embeddings, vector databases (Qdrant, Pinecone, Weaviate, OpenSearch, or pgvector), retrieval, and re-ranking.
  • Hands-on experience building agentic workflows — LLM agents that call tools, reason across multiple steps, and autonomously complete multi-stage tasks with appropriate safeguards.
  • Experience with fine-tuning and adaptation workflows — LoRA, QLoRA, instruction tuning, or preference tuning — and with evaluating model outputs rigorously rather than by demo.

Engineering & Platform Skills

  • Solid LLM tooling fluency — LangChain or LangGraph, LlamaIndex, DSPy, Hugging Face, and the judgment to pick the right tool rather than adopt reflexively.
  • Prompt engineering craft — system prompts, few-shot examples, chain-of-thought, structured output schemas, and tool/function calling.
  • Comfort working with unstructured data — extracting, classifying, and generating structured outputs from text-heavy inputs, including documents and forms.
  • Cloud and deployment fluency — AWS preferred (including Bedrock), plus containerization (Docker), and familiarity with self-hosted LLM serving (vLLM, TGI, Ollama, or similar).
  • Evaluation discipline — ability to write tests for non-deterministic systems, build golden sets, and reason about output quality at scale.
  • Strong debugging instincts for LLM-specific failure modes — hallucinations, retrieval gaps, prompt drift, and latency spikes.

Security & Regulated-Industry Awareness

  • Working awareness of LLM security concerns — prompt injection, data exfiltration, output filtering, and PII handling.

Preferred Qualifications

  • Experience in fintech, lending, banking, healthcare, or another regulated or data-sensitive industry.
  • Familiarity with document understanding models (LayoutLM, Donut, Nougat) and modern OCR tooling (Textract, Tesseract, or equivalents).
  • Background in NLP tasks such as named entity recognition, classification, or semantic similarity.
  • Experience with LLaMA-family open-weight models and self-hosted serving via Ollama or vLLM.
  • Experience contributing to a shared AI platform (prompt registry, evaluation harness, routing layer) used by multiple product teams.

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