{"id":1147738,"url":"https://alion.io/job/bmc-software-lead-software-engineer-agenticai","title":"Lead Software Engineer - AgenticAI","company":{"id":58475,"name":"BMC Software","domain":"bmc.com","url":"https://alion.io/company/bmc-software","size_band":"5000+","is_staffing_agency":false,"is_intermediary":false,"ats_vendor":"Avature","truth_index":{"grade":"A","score":100,"open_postings":9,"ghost_share":0,"stale_share":0,"repost_share":0.111,"time_to_fill_p50_days":6,"computed_at":"2026-09-23T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":152925,"max":254875,"currency":"USD","period":"year","gross":null,"usd_annual":254875},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"FAISS","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Milvus","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Tool Use","optional":false},{"name":"Vertex AI","optional":false},{"name":"Weaviate","optional":false},{"name":"DPO","optional":true},{"name":"GRPO","optional":true},{"name":"Kubernetes","optional":true},{"name":"LoRA","optional":true},{"name":"PEFT","optional":true},{"name":"PPO","optional":true},{"name":"QLoRA","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"RLHF","optional":true},{"name":"SFT","optional":true}],"status":"live","first_seen_at":"2026-09-23T16:10:52Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-09-23T19:56:35Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"CareerArc Code\nCA-BS\nHybrid: #LI-Hybrid\nBMC 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.\nWe are looking for a Lead AI Engineer to help build our next generation Agentic AI platform from 0-1. This is a hands on, delivery driven role for an engineer who has shipped AI powered products into real enterprise environments, understands the trade offs of production AI systems, and takes ownership of outcomes, not just models or demos.\nYou will work alongside our VP of Engineering, VP of AI, senior engineers, and product leadership to define and build the core AI systems of the platform. You will spend most of your time designing, coding, and shipping production grade AI capabilities used by external B2B customers. Success is measured by reliability, controllability, cost efficiency, and customer impact, not novelty.\n\nHow YOU will contribute to BMC’s and your own success\nBuild and evolve agentic AI systems that reason, plan, execute, and adapt in production environments.\nLead AI driven features from concept to production in a true 0-1 product environment.\nWrite and review high quality production code (Python first) across AI pipelines, inference services, orchestration layers, and supporting systems.\nImplement prompt engineering, tool use, memory, evaluation, and guardrails as first class engineering concerns, not experiments.\nContribute to the design of agent frameworks that balance autonomy with determinism, observability, and safety.\nMake pragmatic architectural trade offs across latency, cost, accuracy, scalability, and maintainability.\nIntegrate and operate LLMs (commercial and/or open source) including model selection, fine tuning strategies, embeddings, retrieval (RAG), and inference optimization.\nAddress real world issues: hallucinations, drift, prompt regressions, failure modes, and customer trust.\nDeploy and operate AI services across cloud platforms (AWS, Azure, GCP), including secure enterprise integrations and customer specific deployments.\nEnsure the platform is shippable, debuggable, and supportable - not fragile or research grade.\nAct with strong ownership: identify gaps, propose solutions, and move forward without waiting for perfect requirements.\n\nTo ensure you’re set up for success, you will bring the following skillset & experience\n6+ years of professional software development experience, with significant time shipping B2B products used by external customers.\nStrong software engineering foundation with expert level Python and experience designing production systems.\nProven experience building, deploying, and operating AI powered products in production,\nHands on experience with LLMs and GenAI systems in real applications (e.g., agents, copilots, automation, decision systems).\nUnderstanding of at least several of the following:\nAgent frameworks and orchestration\nPrompt engineering and tool use patterns\nRAG architectures and vector search\nModel evaluation, feedback loops, and monitoring\nSafety, guardrails, and enterprise controls\nHands on experience with multiple of the following in real systems:\nLangGraph and/or LangChain\nLlamaIndex\nVector databases (e.g., Pinecone, Weaviate, FAISS, Milvus)\nPrompt engineering as a managed, versioned, testable artifact\nExperience deploying and operating LLMs using:\nAWS SageMaker, Vertex AI, or equivalent managed platforms\nDirect API integrations (OpenAI, Anthropic)\nExperience designing multi agent systems or complex agent workflows.\nExperience commercializing AI features under enterprise constraints (security, compliance, uptime).\nComfort operating in ambiguity and making decisions with incomplete information.\nNice to have (our team can help you develop these)\nContributions to open source GenAI tooling or internal frameworks used at scale.\nExperience with supervised fine tuning, parameter efficient tuning methods (LoRA, QLoRA), reinforcement learning (RLHF) and preference optimization (PPO, DPO, GRPO).\nExperience deploying LLMs at scale (Kubernetes, model serving, GPU optimization).\nOur commitment to you!\nBMC’s culture is built around its people. We have 6000+ brilliant minds working together across the globe. You won’t be known just by your employee number, but for your true authentic self. BMC lets you be YOU!\nIf after reading the above, You’re unsure if you meet the qualifications of this role but are deeply excited about BMC and this team, we still encourage you to apply! We want to attract talents from diverse backgrounds and experience to ensure we face the world together with the best ideas!\nBMC is committed to equal opportunity employment regardless of race, age, sex, creed, color, religion, citizenship status, sexual orientation, gender, gender expression, gender identity, national origin, disability, marital status, pregnancy, disabled veteran or status as a protected veteran. If you need a reasonable accommodation for any part of the application and hiring process, visit the accommodation request page.\nBMC Software maintains a strict policy of not requesting any form of payment in exchange for employment opportunities, upholding a fair and ethical hiring process.\nThe annual base salary range represents the low and high end of the BMC salary range for this position. Actual salaries depend on a wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training, licensure, and certifications; and other business and organizational needs.\nThe range listed is just one component of BMC's employee compensation package. Other rewards may include a variable plan and country specific benefits.\nAt BMC, it is not typical for an individual to be hired at /near the top of the range. A reasonable estimate of the current range is $152,925 - $254,875\nMin salary\n152,925\nMid point salary\n203,900\nMax salary\n254,875\nMin Salary - NEW\n152,925\nMax Salary - NEW\n254,875","description_format":"text","description_chars":6240,"description_truncated":false,"requirements":{"experience_years_min":6,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Infrastructure","DevOps","IT Management"],"lifecycle":[{"event":"open","at":"2026-09-23T16:10:52Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":6,"reasons":["conf:6","win:early"],"computed_at":"2026-09-24T02:53:55Z"},"pay":{"stated_usd_annual":254875,"is_top_pay":true},"html_url":"https://alion.io/job/bmc-software-lead-software-engineer-agenticai","json_url":"https://alion.io/job/bmc-software-lead-software-engineer-agenticai.json","meta":{"generated_at":"2026-09-24T02:53:55Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}