Description :

Role : Sr. Software Engineer - AI Native Platform

Location : Hyderabad

Mode : Work from office

Night shift : 7 p.m. to 4 a.m.

Exp : 6 + years

What You Will Work On :

- Platformized agentic workflows : Design and build reusable agent harnesses and orchestration services that other teams can plug into, rather than one-off bots.

- Framework evaluation and standardization : Evaluate, integrate, and standardize agent and orchestration frameworks (e.g., LangGraph, Amazon Bedrock Agent Framework/AgentCore) as core building blocks for our AI-native platform.

- Company-wide knowledge graph : Build ingestion pipelines, storage models, and APIs that expose LLM-ready context as a shared platform capability.

- Internal developer platform : Evolve our internal developer platform (Minerva/Vulcan/Veho Build) into the primary way to discover, consume, and safely extend internal APIs, with first-class AI/agent primitives.

- Security and guardrails : Implement cross-cutting policies (authZ, rate limits, capability scopes, audit trails) to ensure AI-powered features are safe by default.

- GitHub-native delivery : Build services that standardize how code, agents, and workflows move from branch to production via PRs, checks, and automated review.

- MCP server ecosystem : Operate a fleet of domain-specific MCP servers as platform components with clear SLAs, observability, and lifecycle management.

Responsibilities :

- Design, build, and operate scalable, multi-tenant platform services used by product, operations, and engineering teams.

- Develop and evolve APIs and systems across edge runtimes and cloud environments.

- Architect distributed systems spanning edge runtimes, cloud providers, and internal platforms.

- Embed AI and LLM-powered capabilities into platform surfaces (e.g., Vulcan, CI/CD, Slack), enabling safe agent workflows and tool use.

- Define standards, best practices, and reference implementations for building AI-native features at Veho.

What Were Looking For :

- 6+ years of software engineering experience with a focus on backend or platform systems.

- Strong fundamentals in APIs, distributed systems, and security for multi-tenant environments.

- Hands-on experience with LLMs, agent frameworks, or AI tooling (e.g., LangGraph, Amazon Bedrock Agent Framework/AgentCore, OpenAI, Anthropic) and a desire to treat them as platform primitives, not just product features.

- Experience building or contributing to internal platforms, API gateways, or developer tooling (e.g., GitHub-based workflows, CI/CD).

- Familiarity with GraphQL, service-to-service communication patterns, and observability for complex systems.

- Curiosity about the rapidly evolving AI ecosystem and a bias toward pragmatic infrastructure that teams readily adopt

- Experience with MCP or similar multi-tool/agent orchestration patterns in production.

- Background in platform security (fine-grained authorization, rate limiting, isolation boundaries).

- Prior work with AWS or GCP AI/agent services as part of a broader platform or developer experience initiative.

- Experience building internal Slack apps or workflow automation that integrate with platform services.