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oracle

Senior Platform Software Engineer

Oracle
Bengaluru, IND
Full-time
Senior · 5+ years experience
Onsite
Discovered Yesterday
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Qualifications

  • Career Level - IC3
  • Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or a related technical field, with 5+ years experience.
  • Strong professional experience designing and building large-scale distributed systems, developer platforms, cloud services, or enterprise software products.
  • Hands-on experience building applications using large language models, including prompt design, structured outputs, function calling, tool use, retrieval-augmented generation, or AI workflow orchestration.
  • Practical understanding of Agentic AI patterns, including planning, reasoning loops, task decomposition, tool invocation, memory, context management, agent state, and autonomous or semi-autonomous execution.
  • Strong programming experience in one or more languages such as Java, Python, Go, or similar.
  • Experience building developer-facing tools such as CLIs, SDKs, APIs, IDE extensions, build systems, CI/CD platforms, testing frameworks, observability tools, infrastructure-as-code tooling, or cloud development platforms.
  • Strong understanding of modern software development workflows, including source control, code review, testing, build automation, deployment pipelines, release management, and production operations.
  • Experience with cloud-native architecture, including microservices, APIs, containers, distributed systems, asynchronous workflows, authentication, authorization, and service observability.
  • Familiarity with AI/ML infrastructure components such as embedding models, vector databases, model serving, model evaluation, telemetry, and experimentation frameworks.
  • Ability to reason about risks in AI-powered developer tools, including incorrect code generation, hallucinated APIs, prompt injection, unsafe tool execution, data leakage, permission misuse, and unreliable automation.
  • Demonstrated ability to lead complex technical projects independently, influence architecture across teams, and deliver high-quality production systems.
  • Strong written and verbal communication skills, with the ability to explain complex technical decisions to engineering, product, and leadership audiences.

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.
  • Provide technical leadership through design documents, architecture reviews, code reviews, mentoring, prototyping, and cross-team technical alignment.
  • Stay current with advances in Agentic AI, LLM application design, AI coding assistants, developer productivity tools, cloud-native development, and responsible AI, and apply them pragmatically to OCI products.

Preferred Qualifications

  • Experience building AI coding assistants, developer copilots, autonomous debugging agents, test generation systems, build failure analyzers, cloud troubleshooting agents, or AI-powered DevOps tools.
  • Experience with agent frameworks or orchestration technologies such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or custom agent runtimes.
  • Experience with commercial or open-source 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, cloud service documentation, build artifacts, logs, metrics, traces, and runtime telemetry.
  • Deep understanding of developer experience, developer productivity, software engineering workflows, and cloud application development.
  • Experience with OCI, especially in areas such as developer tools, DevOps, cloud automation, identity, observability, infrastructure provisioning, networking, compute, storage, or managed AI services.
  • Experience with Kubernetes, containers, Terraform, CI/CD systems, workflow engines, message queues, distributed job execution, or service deployment platforms.
  • Knowledge of secure software supply chain practices, including artifact integrity, dependency scanning, secrets handling, policy enforcement, provenance, and deployment governance.
  • Experience building RAG systems with semantic retrieval, hybrid search, reranking, chunking strategies, grounding validation, citation-aware responses, and access-controlled retrieval.
  • Experience evaluating LLM and agentic systems using golden datasets, synthetic test generation, human review, automated scoring, red teaming, online experimentation, and regression testing.
  • Experience optimizing AI-powered systems for latency, throughput, reliability, token efficiency, cost, model selection, and service availability.
  • Track record of technical leadership through architecture ownership, patents, publications, open-source contributions, platform delivery, or high-impact developer tooling initiatives.
  • Experience mentoring engineers and raising the engineering bar across a team, platform, or organization.

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