This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Agentic Platform Engineer II based in India.
This is a high-impact engineering role focused on building the shared platform that enables teams to develop and operate AI agents at scale. You will shape how retrieval pipelines, agent orchestration, MCP servers, model access, evaluation, and observability are designed and governed. Working primarily with Python, Kubernetes, and Google Cloud, you will create reusable capabilities that accelerate AI adoption across the organization. The role combines hands-on engineering, platform architecture, security, developer experience, and technical leadership. You will build proofs of concept, establish standards, and help internal teams move successful solutions into production. You’ll work in a highly collaborative, remote environment alongside teams adopting increasingly sophisticated agentic technologies. This is an opportunity to influence the foundations of an AI-first engineering ecosystem while solving complex, real-world platform challenges.
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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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