Job Description

Accountabilities

• Build and evolve an internal Agentic Platform, identifying recurring engineering needs and turning them into reusable capabilities, paved paths, and sensible defaults.
• Design, develop, and operate internal MCP servers, including authentication, tool and schema design, versioning, testing, scaffolding, templates, and registries.
• Build the platform infrastructure for remote AI agents, covering deployment, scheduling, credentials, observability, rate limiting, lifecycle management, and safe retirement.
• Establish security and governance guardrails for autonomous agents, including scoped permissions, human approval workflows, sandboxing, audit logging, spending controls, and blast-radius limitations.
• Lead technical approaches for retrieval-augmented generation, including ingestion, chunking, embeddings, vector stores, incremental synchronization, and retrieval-quality measurement.
• Own evaluation and observability practices for AI systems through evaluation harnesses, golden datasets, regression testing, prompt versioning, and instrumentation using relevant observability platforms.
• Improve the agentic developer experience through internal tooling, skills and plugin libraries, code-review agents, remediation agents, and fleet-wide engineering automation.
• Extend and operate the centralized LLM gateway, supporting model and provider coverage, secure access, routing, governance, PII monitoring, access controls, and cost attribution.
• Develop reference implementations and proofs of concept that demonstrate scalable patterns before transitioning ownership to production engineering teams.
• Establish engineering standards and playbooks, mentor teams adopting AI capabilities, advise on build-versus-buy decisions, and participate in an on-call rotation for platform services.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field; a Master’s degree is preferred.
• 8+ years of professional software engineering experience, including at least 2 years building production LLM-powered systems and 2+ years in a senior engineering or technical leadership role.
• Strong production-grade Python skills, along with the ability to confidently read and modify large Java or Kotlin codebases and their build tooling; Scala is a plus.
• Strong TypeScript/Node.js experience is preferred, particularly for AI and platform development.
• Hands-on experience building MCP servers or clients, including tool and schema design, authentication, and secure integrations.
• Experience with agent orchestration frameworks such as LangGraph or equivalent, including context and state management.
• Proven production experience with RAG, vector stores such as PostgreSQL/pgvector, embedding models, chunking strategies, incremental synchronization, and retrieval-quality assessment.
• Experience evaluating non-deterministic AI systems through evaluation harnesses, regression suites, quality gates, prompt versioning, and analysis of latency and cost.
• Practical experience with agentic coding tools such as Claude Code or comparable technologies, with a clear understanding of their strengths and failure modes.
• Strong security awareness for agentic systems, including prompt-injection defenses, sandboxed execution, scoped credentials, audit logging, and blast-radius containment.
• Hands-on Kubernetes and cloud experience, ideally with GCP technologies such as GKE, IAM, GCS, Cloud SQL, Pub/Sub, and BigQuery.
• Familiarity with GitLab CI/CD, Terraform, Docker, and observability tools such as Datadog, Prometheus, and OpenTelemetry.
• Strong platform-engineering mindset, with the ability to transform business problems into reusable capabilities, validate ideas through focused proofs of concept, and document standards clearly.
• Excellent written and verbal English communication skills, with the ability to collaborate effectively across technical and business teams.
• Experience working with US-based business teams and willingness to overlap 2–3 hours with Pacific Time business hours.
• Ability to participate in an on-call rotation and operate effectively in a collaborative, high-trust environment.
• Nice-to-have experience includes internal developer platforms, replacing third-party SaaS or AI solutions with in-house capabilities, large-scale JVM migrations, workflow orchestration platforms, no-code/low-code automation, open-source AI contributions, or AI governance in regulated industries.

Benefits

• Annual compensation range of ₹40,50,000 – ₹56,70,000 INR, depending on experience, skills, knowledge, market alignment, and location.
• Fully remote work arrangement in India.
• Comprehensive benefits supporting health, life, and financial well-being.
• Medical and accident insurance.
• Retiral benefits.
• 12 company-paid holidays plus 2 flexible holidays.
• Privilege/earned leave and casual/sick leave.
• Paid maternity and paternity leave.
• Company-supported wellness initiatives and weekly wellness events.
• Opportunity to work on advanced agentic AI infrastructure with significant technical ownership and organizational impact.
• Collaborative, inclusive culture that values diverse perspectives, autonomy, accountability, and continuous growth.
• Exposure to complex AI, cloud, distributed systems, platform engineering, and developer productivity challenges.
• Opportunities to mentor others, shape technical standards, and influence the adoption of emerging AI technologies.