{"id":3196993,"url":"https://alion.io/job/oracle-senior-platform-software-engineer-67","title":"Senior Platform Software Engineer","company":{"id":53,"name":"Oracle","domain":"oracle.com","url":"https://alion.io/company/oracle","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":89,"open_postings":314,"ghost_share":0,"stale_share":0.627,"repost_share":0.003,"time_to_fill_p50_days":9,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18500,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":159},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"Go","optional":false},{"name":"Hallucination","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Anthropic","optional":true},{"name":"AutoGen","optional":true},{"name":"Cohere SDK","optional":true},{"name":"CrewAI","optional":true},{"name":"Gemini","optional":true},{"name":"Hybrid Search","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Llama","optional":true},{"name":"LlamaIndex","optional":true},{"name":"Mistral","optional":true},{"name":"OpenAI","optional":true},{"name":"Red Teaming","optional":true},{"name":"Reranking","optional":true},{"name":"Terraform","optional":true}],"status":"closed","first_seen_at":"2026-10-24T04:03:10Z","employer_posted_date":"2026-10-24","last_verified_at":"2026-10-31T12:42:26Z","board_verified":false,"closed_at":"2026-10-31T12:42:26Z","days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"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.\nIn 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.\nThis 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.\n Key Responsibilities\nDesign, build, and operate Agentic AI-powered developer tools for the OCI Developer Tools organization.\nDevelop AI agents that assist with code authoring, debugging, test generation, build failure analysis, deployment guidance, infrastructure automation, cloud diagnostics, and developer workflow optimization.\nBuild systems that combine LLMs, retrieval-augmented generation, tool calling, workflow orchestration, code intelligence, structured outputs, and OCI service APIs.\nCreate agent workflows that can reason across source code, SDKs, APIs, CLI commands, documentation, build logs, telemetry, repositories, deployment artifacts, and cloud resource metadata.\nDesign 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.\nPartner with product managers, UX designers, developer relations, cloud service teams, security, and infrastructure teams to translate developer pain points into scalable AI product capabilities.\nBuild 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.\nContribute to platform architecture for AI-assisted development, including agent runtimes, context management, prompt orchestration, model routing, evaluation pipelines, telemetry, and feedback loops.\nEnsure AI-powered developer tools meet OCI standards for security, privacy, reliability, compliance, operational readiness, scalability, and enterprise-grade quality.\nProvide technical leadership through design documents, architecture reviews, code reviews, mentoring, prototyping, and cross-team technical alignment.\nStay 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.\nRequired Qualifications\nBachelor’s or Master’s degree in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or a related technical field, with 5+ years experience.\nStrong professional experience designing and building large-scale distributed systems, developer platforms, cloud services, or enterprise software products.\nHands-on experience building applications using large language models, including prompt design, structured outputs, function calling, tool use, retrieval-augmented generation, or AI workflow orchestration.\nPractical understanding of Agentic AI patterns, including planning, reasoning loops, task decomposition, tool invocation, memory, context management, agent state, and autonomous or semi-autonomous execution.\nStrong programming experience in one or more languages such as Java, Python, Go, or similar.\nExperience 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.\nStrong understanding of modern software development workflows, including source control, code review, testing, build automation, deployment pipelines, release management, and production operations.\nExperience with cloud-native architecture, including microservices, APIs, containers, distributed systems, asynchronous workflows, authentication, authorization, and service observability.\nFamiliarity with AI/ML infrastructure components such as embedding models, vector databases, model serving, model evaluation, telemetry, and experimentation frameworks.\nAbility 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.\nDemonstrated ability to lead complex technical projects independently, influence architecture across teams, and deliver high-quality production systems.\nStrong written and verbal communication skills, with the ability to explain complex technical decisions to engineering, product, and leadership audiences.\nPreferred Qualifications\nExperience building AI coding assistants, developer copilots, autonomous debugging agents, test generation systems, build failure analyzers, cloud troubleshooting agents, or AI-powered DevOps tools.\nExperience with agent frameworks or orchestration technologies such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or custom agent runtimes.\nExperience with commercial or open-source LLM ecosystems such as OpenAI, Anthropic, Google Gemini, Cohere, Meta Llama, Mistral, or enterprise-hosted models.\nExperience designing systems that reason over large codebases, dependency graphs, APIs, SDKs, cloud service documentation, build artifacts, logs, metrics, traces, and runtime telemetry.\nDeep understanding of developer experience, developer productivity, software engineering workflows, and cloud application development.\nExperience with OCI, especially in areas such as developer tools, DevOps, cloud automation, identity, observability, infrastructure provisioning, networking, compute, storage, or managed AI services.\nExperience with Kubernetes, containers, Terraform, CI/CD systems, workflow engines, message queues, distributed job execution, or service deployment platforms.\nKnowledge of secure software supply chain practices, including artifact integrity, dependency scanning, secrets handling, policy enforcement, provenance, and deployment governance.\nExperience building RAG systems with semantic retrieval, hybrid search, reranking, chunking strategies, grounding validation, citation-aware responses, and access-controlled retrieval.\nExperience evaluating LLM and agentic systems using golden datasets, synthetic test generation, human review, automated scoring, red teaming, online experimentation, and regression testing.\nExperience optimizing AI-powered systems for latency, throughput, reliability, token efficiency, cost, model selection, and service availability.\nTrack record of technical leadership through architecture ownership, patents, publications, open-source contributions, platform delivery, or high-impact developer tooling initiatives.\nExperience mentoring engineers and raising the engineering bar across a team, platform, or organization.\n Career Level - 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