Senior Platform Software Engineer
Senior platform engineer (IC3) on Oracle's Developer Platform Builder Tools team designing, building, and operating Agentic AI developer tools for OCI — combining LLMs, RAG, tool calling, and workflow orchestration to help engineers code, debug, and automate cloud workflows. Needs 5+ years building distributed systems and LLM applications in Java, Python, or Go.
- Compensation
- Not disclosed
- Location
- BENGALURU, KARNATAKA, India
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Must have
- Bachelor's or Master's degree in CS/Computer Engineering/AI/ML or related field, with 5+ years experience
- Strong experience designing and building large-scale distributed systems, developer platforms, cloud services, or enterprise software
- Hands-on experience building LLM applications: prompt design, structured outputs, function calling, tool use, RAG, AI workflow orchestration
- Practical understanding of Agentic AI patterns: planning, reasoning loops, task decomposition, tool invocation, memory, context management
- Strong programming experience in one or more languages such as Java, Python, Go, or similar
- Experience building developer-facing tools: CLIs, SDKs, APIs, IDE extensions, build systems, CI/CD, testing frameworks, observability or IaC tooling
- Strong understanding of modern software development workflows: source control, code review, testing, build automation, deployment pipelines, production operations
- Experience with cloud-native architecture: microservices, APIs, containers, distributed systems, async workflows, authn/authz, observability
- Familiarity with AI/ML infrastructure: embedding models, vector databases, model serving, model evaluation, telemetry, experimentation frameworks
- Ability to reason about risks in AI-powered developer tools: incorrect code generation, hallucinated APIs, prompt injection, unsafe tool execution, data leakage
- Demonstrated ability to lead complex technical projects independently and influence architecture across teams
Nice to have
- Experience building AI coding assistants, copilots, debugging agents, test generation systems, or AI-powered DevOps tools
- Experience with agent frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or custom agent runtimes
- Experience with LLM ecosystems such as OpenAI, Anthropic, Google Gemini, Cohere, Meta Llama, Mistral, or enterprise-hosted models
- Experience designing systems that reason over large codebases, dependency graphs, APIs, SDKs, documentation, build artifacts, logs, and telemetry
- Deep understanding of developer experience, developer productivity, and cloud application development
- Experience with OCI: developer tools, DevOps, cloud automation, identity, observability, networking, compute, storage, or managed AI services
- Experience with Kubernetes, containers, Terraform, CI/CD systems, workflow engines, message queues, or distributed job execution
- Knowledge of secure software supply chain practices: artifact integrity, dependency scanning, secrets handling, policy enforcement
- Experience building RAG systems: semantic retrieval, hybrid search, reranking, chunking, grounding validation, access-controlled retrieval
- Experience evaluating LLM/agentic systems: golden datasets, synthetic tests, human review, red teaming, regression testing
- Experience optimizing AI systems for latency, throughput, reliability, token efficiency, cost, and model selection
- Track record of technical leadership: architecture ownership, patents, publications, open-source contributions, or high-impact tooling
Full description
The Developer Platform Builder Tools organization is responsible for building the next generation of developer productivity platforms, intelligent development workflows, and AI-powered engineering tools that accelerate software delivery across the enterprise. We are seeking a highly motivated Software Development Engineer (IC3) to design, build, and operate scalable platform services and developer tools that enhance engineering productivity through automation and AI-driven capabilities.
In this role, you will design and build Agentic AI capabilities that help developers understand complex cloud systems, generate and improve code, troubleshoot failures, automate repetitive workflows, reason over logs and documentation, interact with OCI services, and safely execute multi-step development tasks. These systems will combine large language models, retrieval-augmented generation, tool use, workflow orchestration, code intelligence, cloud APIs, and enterprise-grade safety controls.
This is an excellent opportunity for engineers who are passionate about building large-scale distributed systems, developer platforms, and AI-enabled engineering solutions that improve how thousands of engineers build, deploy, and operate software.
Key Responsibilities
- Design, build, and operate Agentic AI-powered developer tools for the OCI Developer Tools organization.
- Develop AI agents that assist with code authoring, debugging, test generation, build failure analysis, deployment guidance, infrastructure automation, cloud diagnostics, and developer workflow optimization.
- Build systems that combine LLMs, retrieval-augmented generation, tool calling, workflow orchestration, code intelligence, structured outputs, and OCI service APIs.
- Create agent workflows that can reason across source code, SDKs, APIs, CLI commands, documentation, build logs, telemetry, repositories, deployment artifacts, and cloud resource metadata.
- Design safe and reliable agent execution patterns, including human-in-the-loop approval, guardrails, access control, audit logging, tool-use constraints, error recovery, and policy-aware automation.
- Partner with product managers, UX designers, developer relations, cloud service teams, security, and infrastructure teams to translate developer pain points into scalable AI product capabilities.
- Build evaluation frameworks for developer-facing AI systems, including task success, code correctness, grounding quality, tool-call accuracy, hallucination detection, latency, cost, safety, and regression metrics.
- Contribute to platform architecture for AI-assisted development, including agent runtimes, context management, prompt orchestration, model routing, evaluation pipelines, telemetry, and feedback loops.
- Ensure AI-powered developer tools meet OCI standards for security, privacy, reliability, compliance, operational readiness, scalability, and enterprise-grade quality.