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Tech Lead Gen AI

India, Bengaluru · Job Posted June 08, 2026
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Job Description

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

Job Responsibility

  • Architecture & Systems Design: Design and own event-driven, micro-services architectures on GCP
  • Architect end-to-end RAG pipelines - ingestion, chunking, retrieval, and generation - for production workloads
  • Define and enforce network and access security patterns: IAP, VPC-SC, Secret Manager
  • Author Architecture Decision Records (ADRs) and enforce Definition of Done (DoD) standards
  • Trade-offs, Cost & Performance: Lead LLM selection decisions - Vertex AI vs. open-source - with structured cost-benefit framing
  • Optimize GenAI run costs through token budgeting, embedding cache strategies, and model tiering
  • Own scalability design for Cloud Run workloads, including cold-start mitigation and load-testing strategy
  • Translate architectural trade-offs into clear stakeholder communication
  • Data & Document Quality: Design source modeling strategies across Drive, GCS, and Vector Search
  • Define and enforce chunking strategies and Registry governance for document pipelines
  • Proactively identify and retire technical debt
  • maintain a prioritized remediation backlog
  • Technical Leadership: Mentor engineers through code reviews, pair programming, and design walkthroughs
  • Serve as the primary technical interface with FR Core Team and AI sponsors
  • Champion engineering standards and drive adoption of best practices across the squad

Requirements

  • 8+ years of software engineering experience, with 3+ years in AI/ML engineering or GenAI platform roles
  • Production-grade RAG system delivery - from ingestion through retrieval to generation - not just prototyping
  • Deep GCP proficiency: Vertex AI, Cloud Run, Pub/Sub, VPC-SC, IAP, Secret Manager
  • Hands-on experience with vector stores: Vertex AI Vector Search, Weaviate, Pinecone, or equivalent
  • LLM evaluation and selection experience: commercial (Gemini, GPT-4) and open-source (Mistral, LLaMA)
  • Architectural authoring: ADRs, tech specs, system diagrams for engineering and cross-functional audiences
  • Demonstrated team lead experience: code reviews, technical mentorship, squad-level design ownership

Nice to have

  • Experience with embedding cache optimization and token-level cost management at scale
  • Knowledge of GCS-based document pipelines and chunking strategy design for retrieval quality
  • Familiarity with LLM observability tooling: LangSmith, Arize, Weights & Biases
  • Exposure to enterprise AI governance frameworks or FR Core delivery models
  • Google Cloud Professional ML Engineer or Cloud Architect certification

What we offer

  • Flexibility, with remote and hybrid work options (country-dependent)
  • Career advancement, with international mobility and professional development programs
  • Learning and development, with access to cutting-edge tools, training and industry experts

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