{"id":774207,"url":"https://alion.io/job/planera-senior-ai-agent-engineer","title":"Senior AI Agent Engineer","company":{"id":687919,"name":"Planera","domain":"planera.io","url":"https://alion.io/company/planera-2","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"D","score":52,"open_postings":10,"ghost_share":0.8,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-28T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":136000,"max_usd":243000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":222},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Caching","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"WebSockets","optional":false},{"name":"Amazon S3","optional":true},{"name":"Docker","optional":true},{"name":"Flask","optional":true},{"name":"GitLab CI","optional":true},{"name":"JavaScript","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-06-29T23:59:28Z","employer_posted_date":"2026-06-29","last_verified_at":"2026-09-28T23:45:28Z","board_verified":true,"closed_at":null,"days_open":91,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":90},"description":"About the Role\nJoin Planera to build Manny, our AI scheduling assistant, and shape how construction schedulers work with AI on a modern Critical Path Method platform. You will own agent features end to end: designing and evolving the LangGraph/LangChain agent, engineering prompts and tools, integrating LLMs across providers, and holding response quality to a high bar with a real evaluation and observability stack. This is a hands-on applied AI role with a strong software engineering foundation and a focus on reliability, behavior quality, and user impact. You will work directly with the CTO and the lead AI engineer.\nKey Responsibilities\nDesign, build, and own Manny features end to end across the agent backend, tools, and UI\n\nImprove agent behavior, reliability, and answer quality through prompt engineering, tool design, and changes to the agent control flow\n\nEvolve the agent architecture: ReAct loop, routing and controller logic, multi-node graphs, tool selection, and streaming responses\n\nIntegrate and tune LLMs across providers (Anthropic, OpenAI, Google), balancing quality, latency, and cost, including prompt caching and model selection\n\nDesign and extend Manny's tool surface through the MCP server that connects the agent to Planera's scheduling services\n\nBuild and own the evaluation loop: golden datasets, automated evaluators, snapshot-based replay, and offline and online quality metrics\n\nImplement observability for agent runs with tracing, metrics, and structured logging, and use it to debug and improve behavior in production\n\nEnsure safe, sandboxed execution of model-generated code and safe handling of tool side effects and mutations\n\nCollaborate with product, backend, and frontend to deliver AI features end to end\n\nRequirements\n4+ years of software engineering experience, including recent hands-on work building production LLM features.\n\nStrong proficiency in Python building production services\n\nHands-on experience building agentic systems with LLMs: tool and function calling, ReAct or similar loops, and orchestration frameworks such as LangChain/LangGraph\n\nPractical prompt engineering skill: shaping model behavior reliably, debugging failures from traces, and managing large prompts and token cost\n\nExperience evaluating LLM systems: building datasets, writing evaluators, catching regressions, and using tracing and observability tooling\n\nExperience with the Model Context Protocol (MCP) or building tool and function-calling integrations for LLMs\n\nSolid understanding of API design (REST, websockets, SSE and streaming) and interservice communication\n\nProduct mindset with a focus on user impact and pragmatic tradeoffs\n\nExcellent remote communication skills\n\nPreferred\nExperience with MongoDB and Redis\n\nCloud experience (AWS or GCP), containers, and CI/CD\n\nGo experience, as most of our backend systems are written in Go, including the MCP tool server\n\nPractical experience with retrieval and augmentation (RAG), embeddings, and vector stores\n\nFamiliarity with LangSmith or comparable LLM evaluation and tracing platforms\n\nFrontend or React familiarity for agent UI work\n\nDomain knowledge in construction tech, project management, or scheduling\n\nTech Stack\nPython (Flask), Go, LangGraph/LangChain, LangSmith, MongoDB, Redis, S3, REST/websockets/SSE, Docker, AWS/GCP, Terraform, GitLab CI/CD\nWhy Join Us\nImpact: Be at the forefront of transforming a $12.1 trillion industry. Build the AI that changes how the world plans and schedules construction.\nCulture: Join a smart, spirited team dedicated to innovation and excellence.\nGrowth: Opportunity for professional growth and career advancement in a fast-paced start-up environment.\nBenefits\nCompetitive salary, stock options, benefits package, and a dynamic work environment.","description_format":"text","description_chars":3771,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Stock options"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Construction","Construction Management Software"],"lifecycle":[{"event":"open","at":"2026-09-11T22:26:27Z"}],"liveness":{"score":12,"band":"cold","label":"Long shot","p_open":1,"p_active":0.445,"p_room":0.28,"age_days":90,"expected_fill_days":40,"reasons":["conf:3","stale_co","win:tail","crowd:"],"computed_at":"2026-09-28T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/planera-senior-ai-agent-engineer","json_url":"https://alion.io/job/planera-senior-ai-agent-engineer.json","meta":{"generated_at":"2026-09-29T04:20:25Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4079,"day_limit":5000,"remaining_today":921,"minute_limit":60,"resets_at":"2026-09-30T00:00:00Z"}}}