AI/ML Engineer

Were hiring: AI Engineer (3+ years) at Fundrev (Bangalore, 6 days/week)

Fundrev is an AI native platform for PE and VC that turns raw deal and portfolio data into decision ready insights for screening, diligence, and monitoring. Were building systems that investment teams can trust under real deadlines and messy data.

This role is for someone who can build product grade AI, not demos.

Location and working model

• Bangalore, in person
• 6 day work week (Mon to Sat)

What youll own

You will own end to end delivery across the application layer and AI pipeline layer: ingestion to orchestration to evaluation to production reliability. Youll work closely with the founders and ship directly to users.

What youll build

AI pipelines at scale

• LLM powered workflows: extraction, classification, summarization, Q&A, reconciliation across sources
• RAG systems: chunking strategies, embedding pipelines, vector search, reranking, citation grounding
• Evaluation and quality: offline test sets, automatic evals, human review loops, regression checks
• Observability: latency, cost, failure modes, drift, and prompt and model performance tracking

Application layer

• APIs and services that make AI features feel fast, reliable, and safe
• Multi tenant data access patterns, permissions, auditability, and traceability
• Workflow engines for long running tasks, retries, idempotency, and backfills

Data and reliability

• Ingestion from documents, spreadsheets, CRMs, and internal systems
• Pipeline design for throughput, correctness, and debuggability
• Guardrails for privacy, security, and compliance minded handling of sensitive investment data

What were looking for (must have)

• 3+ years building backend application systems and production AI or ML pipelines
• Strong Python/React/Node.js engineering and comfort shipping production services
• Experience with LLMs in real products: prompt design, tool use, RAG, structured outputs, failure handling
• Solid fundamentals: data modeling, API design, queues, caching, testing, monitoring
• You can take a fuzzy problem, define the right solution, and ship it without hand holding

Good to have

• Experience with vector databases, search, rerankers, and retrieval evaluation
• Workflow orchestration (queues, schedulers, async workers) and distributed systems patterns
• Experience working with financial or enterprise data where correctness matters
• Cost control and performance tuning for LLM workloads

Compensation

• Competitive base salary
• Meaningful equity
• This is a high ownership seat. If you want maximum learning, real responsibility, and direct impact, youll get it here.

How to Apply: Fill this form at