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Forward Deployed Engineer - Lead

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Description


Key Responsibilities:-


  • Build and maintain ingestion pipelines from BT's source systems (docs, wikis, ticketing, databases)
  • Own ETL/ELT jobs, chunking strategy, embedding generation, and pipeline monitoring
  • Implement data quality checks, deduplication, and access-control tagging on ingested content
  • Manage schema and version changes as BT's underlying systems evolve
  • Implement RAG pipelines, multi-agent orchestration, and prompt/context construction logic
  • Tune retrieval quality (hybrid search, reranking, context window management)
  • Integrate with the client's chosen LLM providers and manage prompt versioning
  • Own latency and cost optimization for inference calls
  • Own deployment (cloud/on-prem per BT's constraints), CI/CD, and environment management
  • Handle auth/SSO, network policies, and compliance requirements specific to BT (telecom-grade security)
  • Set up observabilitylogging, tracing, alertingfor the whole pipeline
  • Manage integration with BT's existing enterprise systems (ticketing, CRM, internal tools)
  • Build evaluation harnesses (accuracy, faithfulness, retrieval precision/recall) for the context pipeline
  • Run regression testing whenever prompts, models, or data sources change
  • Own guardrailsPII detection, hallucination checks, content filtering
  • Publish quality dashboards/reports used in BT governance reviews

Required Skills:-


  • Python and SQL
  • ETL/ELT tooling (Airflow, dbt, or equivalent) and document chunking/embedding pipelines
  • Vector databases (Pinecone, Weaviate, pgvector, or similar) and embedding models
  • RAG architectures, hybrid search, reranking, and context window management
  • Multi-agent orchestration frameworks (LangChain, LangGraph, or similar)
  • Prompt engineering and prompt versioning; working knowledge of major LLM APIs (OpenAI, Anthropic, Azure OpenAI, Bedrock)
  • Cloud platforms (AWS/Azure/GCP) and on-prem deployment patterns; Docker/Kubernetes
  • CI/CD pipelines and environment management
  • SSO/OAuth, enterprise auth, and networking/security fundamentals for regulated environments
  • Observability tooling (Prometheus, Grafana, OpenTelemetry) and building LLM evaluation harnesses
  • Regression testing practices and guardrail/PII-detection tooling
  • 4+ years in data/ML engineering or applied AI, ideally with a prior LLM system in production

Nice to Have: Experience in telecom or another regulated industry; knowledge graphs/ontology-based retrieval; LLM cost/latency optimization (caching, batching, model routing); exposure to enterprise ticketing/CRM platforms (ServiceNow, Salesforce, Jira); experience presenting quality metrics to governance stakeholders.


Interested candidates kindly share your resume directly to Vijayravi.r@prodapt.com with the below details along with updated resume.



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