Lead Software Engineer - Agentic AI & Data
BMC empowers nearly 80% of the Forbes Global 100 to accelerate business value, faster than humanly possible. Our industry-leading portfolio unlocks human and machine potential to drive business growth, innovation, and sustainable success. BMC does this in a simple and optimized way by connecting people, systems, and data that power the world’s largest organizations so they can seize a competitive advantage. Overview BMC is hiring a hands-on Lead Software Engineer - Agentic AI & Data to build its next-generation agentic AI platform. The role suits a senior engineer who has already shipped AI products into enterprise environments and owns outcomes end to end. Success is judged by reliability, controllability, cost-efficiency and customer impact. Key Responsibilities Design, build and evolve agentic systems that reason, plan, execute and adapt in production. Take AI features from concept to production in a 0-1 product setting. Write and review production code (Python-first) across AI pipelines, inference services and orchestration layers. Treat prompt engineering, tool use, memory, evaluation and guardrails as core engineering concerns. Design agent frameworks that balance autonomy with determinism, observability and safety. Make pragmatic trade-offs across latency, cost, accuracy, scalability and maintainability. Integrate and operate commercial and/or open-source LLMs, including model selection, embeddings, RAG and inference optimization. Tackle real-world issues such as hallucinations, drift, prompt regressions and failure modes. Deploy and operate AI services on AWS, Azure and GCP, including secure and customer-specific enterprise deployments. Build scalable inference and orchestration architectures with containers, APIs and distribute systems. Keep the platform shippable, debuggable and supportable, and act with founder-level ownership. Required Skills & Experience 9-10+ years of professional software development, with significant time shipping B2B product to external customers. Expert-level Python or Java and experience designing production systems. Proven record building, deploying and operating AI-powered products in production. Build reusable components, SDKs and APIs for AI integration Hands-on LLM/GenAI experience in real applications (agents, copilots, automation, decision systems). Deep knowledge of several of: agent frameworks and orchestration; agent harness; prompt engineering and tool-use patterns; RAG and vector search; model evaluation, feedback loops and monitoring; safety, guardrails and enterprise controls. Hands-on use of several of: LangGraph/LangChain, LlamaIndex, Google ADK, vector databases (Pinecone, Weaviate, FAISS, Milvus), and prompts managed as versioned, testable artifacts. Experience running LLMs via managed platforms (AWS SageMaker/Bedrock, Vertex AI or similar) and direct APIs (OpenAI, Anthropic). Experience with multi-agent systems or complex agent workflows. Experience commercializing AI features under enterprise constraints (security, compliance, uptime).Experience deploying LLMs at scale (Kubernetes, model serving, GPU optimization). Comfort with ambiguity and decision-making under incomplete information. Ability to mentor junior members Ability to manager stakeholders independently and work across domains and global teams
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