Job SummaryWe are seeking a
Tech Lead - AI Orchestration & Semantic Platforms to drive the design, development, and deployment of advanced agentic systems. This role requires deep expertise in
multi-agent orchestration, semantic retrieval, knowledge graphs, and data foundations, combined with strong backend engineering skills. The Tech Lead will remain hands-on while mentoring engineers, creating reusable patterns, and ensuring production readiness across AI, data, and cloud environments.
Job Description/ Responsibilities/ Years of experience:
Primary Focus- Serve as Master Coordinator for domain agents, semantic retrieval, knowledge graphs, and agent quality.
- Own orchestration, semantic, and data-foundation design.
- Create reusable agent patterns and frameworks for scalability.
Backend Engineering- Develop advanced Python services for multi-step workflows.
- Implement orchestration state management, tool invocation, and fallback handling.
- Build reusable agent patterns for cross-domain execution.
API & Integration- Define standard agent and tool contracts.
- Manage agent registration, deterministic routing, and LLM-assisted routing.
- Enable multi-domain execution with model and platform adapters.
Data Engineering- Use advanced SQL and BigQuery for source discovery and reconciliation.
- Conduct data-gap analysis, business-key validation, and lineage assessment.
- Ensure data quality, freshness, and source-of-truth consistency.
AI & Retrieval- Apply deep RAG expertise for retrieval, reranking, and grounding.
- Assemble prompts/contexts with citation support and hallucination reduction.
- Deliver cross-domain synthesis for enterprise use cases.
Knowledge Graph- Design and manage RDF, SPARQL, and ontology models.
- Work with SHACL, Stardog, and relational-to-semantic mappings.
- Implement semantic versioning and graph promotion strategies.
Cloud & Infrastructure- Deploy agent runtimes on GCP/GKE with secure service identities.
- Configure semantic-platform connectivity and environment setups.
- Manage BigQuery, GCS, and cloud-native integrations.
CI/CD & Release- Implement CI/CD pipelines for agents and knowledge graphs.
- Automate evaluation gates for prompts, tools, mappings, and ontologies.
- Maintain versioned deployment definitions.
Testing & Quality- Evaluate agents for accuracy, relevance, groundedness, completeness, hallucination, latency, and cost.
- Build benchmark scenarios and gold-answer datasets.
Observability & Operations- Implement end-to-end tracing across coordinator, agent, tool, semantic, and data layers.
- Use Langfuse/Grafana for observability, reporting, and model comparisons.
Security & Governance- Enforce identity-aware retrieval and least-privilege data access.
- Establish cross-domain guardrails and auditability.
- Ensure source attribution and prompt-data protection.
Tech Lead Expectations- Remain hands-on while mentoring engineers.
- Drive orchestration, semantic, and data-foundation design.
- Create reusable patterns and ensure production readiness.
- Lead evaluation frameworks and foster technical excellence.
