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BMC Software

IT management software for mainframes

AI Engineer

AI Application EngineeringConfirmed live in the last 24 hours
Full-timePune, Maharashtra, India

About the Job

Requirements

  • 10+ years of professional software development experience, including significant experience shipping B2B products used by external customers.
  • Strong software engineering foundation, expert-level Python proficiency, and experience designing production systems.
  • Proven experience building, deploying, and operating AI-powered products in production rather than only prototypes or research.
  • Hands-on experience with large language models and generative AI systems in real applications such as agents, copilots, automation, or decision systems.
  • Deep understanding of several of the following: agent frameworks and orchestration; prompt engineering and tool-use patterns; retrieval-augmented generation architectures and vector search; model evaluation, feedback loops, and monitoring; safety, guardrails, and enterprise controls.
  • Hands-on experience with multiple of the following in real systems: LangGraph and/or LangChain; LlamaIndex; vector databases such as Pinecone, Weaviate, FAISS, or Milvus; managing, versioning, and testing prompt engineering artifacts; deploying and operating large language models using AWS SageMaker, Vertex AI, or equivalent managed platforms; direct API integrations with OpenAI or Anthropic; designing multi-agent systems or complex agent workflows; commercializing AI features under enterprise security, compliance, and uptime constraints.
  • Ability to operate in ambiguity and make decisions with incomplete information.

Responsibilities

  • Design, build, and evolve agentic AI systems that reason, plan, execute, and adapt in production environments.
  • Take AI-driven features from concept to production in a 0–1 product environment.
  • Write and review production code, primarily in Python, across AI pipelines, inference services, orchestration layers, and supporting systems.
  • Implement prompt engineering, tool use, memory, evaluation, and guardrails as core engineering concerns.
  • Design agent frameworks that balance autonomy with determinism, observability, and safety.
  • Make architectural trade-offs across latency, cost, accuracy, scalability, and maintainability.
  • Integrate and operate commercial and/or open-source large language models, including model selection, fine-tuning strategies, embeddings, retrieval-augmented generation, and inference optimization.
  • Address production issues including hallucinations, drift, prompt regressions, failure modes, and customer trust.
  • Deploy and operate AI services across AWS, Azure, and GCP, including secure enterprise integrations and customer-specific deployments.
  • Design scalable inference and orchestration architectures using containers, APIs, and distributed systems.
  • Ensure the platform is shippable, debuggable, and supportable rather than fragile or research-grade.
  • Identify gaps, propose solutions, and advance work without waiting for perfect requirements.

Desired Qualifications

  • Contributions to open-source generative AI tooling or internal frameworks used at scale.
  • Experience with supervised fine-tuning, parameter-efficient tuning methods such as LoRA and QLoRA, reinforcement learning from human feedback, and preference optimization methods such as PPO, DPO, or GRPO.
  • Experience deploying large language models at scale using Kubernetes, model serving, and GPU optimization.

About the Company

BMC Software

IT management software for mainframes

What BMC Software does: It provides software to manage and optimize large enterprise IT environments, from IBM mainframes to modern cloud systems. How its product works: Its tools monitor, manage, and automate IT infrastructure across mainframes, distributed servers, and cloud platforms, helping teams keep systems running, secure, and efficient. How it stands out from competitors: It has a long track record starting with mainframe software and has grown through targeted acquisitions to offer a broad suite for end-to-end IT operations, spanning on‑premises and cloud, with strategic ownership changes that gave it room to adapt. What its goal is: to help enterprises operate complex IT environments more reliably and efficiently by providing integrated software for mainframes, distributed systems, and cloud management.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Houston, TX
Founded
1980

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