Job Role: AI Systems Engineer (Applied LLM & Knowledge Infrastructure)
Location: Bengaluru-Rajarajeshwari Nagar / Onsite
Organization: MetFlux Research Pvt. Ltd.
Employment Type: Full-time
About MetFlux
MetFlux builds physiology-informed computational infrastructure across clinical deployment (MetSights), translational R&D (MetSolve), and modular AI layers. We design structured reasoning systems, not generic chatbots.
Role Overview
We are hiring an AI Systems Engineer to build and scale production-grade LLM integration + knowledge infrastructure across MetFlux platforms.
This role involves:
- Retrieval-augmented reasoning systems
- Knowledge graph integration
- Clinical + R&D workflow intelligence
- Production deployment of AI services
You will work at the intersection of systems biology, structured knowledge, and applied AI.
Core Responsibilities
1. LLM & RAG Architecture
- Design hybrid retrieval pipelines (vector + graph + structured filters)
- Build schema-aligned embeddings for domain datasets
- Develop prompt orchestration and evaluation frameworks
- Implement structured output enforcement (JSON schema, validators)
2. Knowledge Systems Integration
- Integrate LLMs with:
- Neo4j (knowledge graph)
- Vector databases
- Domain ontologies (YAML/structured taxonomies)
- Build reasoning pipelines that preserve traceability
3. Backend & Deployment
- Develop Python microservices (FastAPI preferred)
- Containerization using Docker
- Deploy on cloud infrastructure (AWS preferred)
- Design logging, versioning, and evaluation loops
4. Model Engineering
- Evaluate open-source models (Llama, Mistral, etc.)
- Perform instruction tuning / LoRA when needed
- Optimize inference cost and performance
- Implement guardrails and hallucination mitigation strategies
Required Skills
- Strong Python backend engineering (production-level)
- Experience building RAG pipelines beyond tutorials
- Experience with:
- LangGraph / LangChain OR custom orchestration
- Vector databases
- Graph databases
- Familiarity with structured knowledge representation
- Understanding of LLM evaluation metrics
- Ability to convert domain logic into machine-readable schemas
Preferred
- Healthcare or biological domain exposure
- Experience working with structured ontologies
- Experience integrating AI into SaaS platforms
- Basic understanding of compliance environments
Experience Level
1–3 years strong applied AI engineering OR demonstrable production-grade portfolio
This role requires system thinking. We value engineers who can design architecture, not just experiment with models.
To Apply
Interested candidates apply to this job post or write to [Confidential Information]
Please attach:
- Your portfolio link with recent projects.
- A short note on a project you built or optimized and what you learned from it.
