{"id":117151,"url":"https://alion.io/job/sitetracker-senior-software-engineer-ai","title":"Senior Software Engineer II - AI","company":{"id":7358,"name":"Sitetracker","domain":"sitetracker.com","url":"https://alion.io/company/sitetracker","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":4,"ghost_share":0,"stale_share":0.5,"repost_share":0.5,"time_to_fill_p50_days":60,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New Delhi, India","Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":38000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":139},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AWS","optional":false},{"name":"FastAPI","optional":false},{"name":"Function Calling","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Node JS","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React Native","optional":false},{"name":"TypeScript","optional":false},{"name":"Apex","optional":true},{"name":"CI/CD","optional":true},{"name":"CrewAI","optional":true},{"name":"Docker","optional":true},{"name":"JavaScript","optional":true},{"name":"LangChain","optional":true},{"name":"Langfuse","optional":true},{"name":"LangGraph","optional":true},{"name":"LangSmith","optional":true},{"name":"LlamaIndex","optional":true},{"name":"LLMOps","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"React.js","optional":true},{"name":"Rest API","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-07-13T15:14:45Z","employer_posted_date":"2026-07-13","last_verified_at":"2026-10-16T22:05:33Z","board_verified":true,"closed_at":null,"days_open":95,"trust":{"level":"ok","repost_count":2,"flags":["repost"],"days_open":94},"description":"The Opportunity\nThis is more than a full-stack role - it's your chance to build the AI layer of the platform the world's infrastructure runs on. Sitetracker is building Scout, our AI product line: production LLM systems and agentic workflows embedded in the software companies like Cox, Telefónica, and EVgo use to deploy critical infrastructure. As a Product Engineer, you'll take AI capabilities from idea to production agent orchestration and model integration on the backend, and the web and mobile experiences that put them in customers' hands.\nThis is shipping real, customer-facing AI , not prototypes or research demos. You'll own features end-to-end, work with frontier models (Anthropic, OpenAI), and see your work land in the hands of enterprise users deploying telecom networks, EV chargers, and renewable energy around the world.\nWhat You’ll do:\nAs a Product Engineer on Scout, you'll hit the ground running and ship customer-facing AI from day one. You'll design, build, test, deploy, and monitor AI product features end-to-end , building agentic LLM systems with multi-agent workflows, tool/function calling, RAG pipelines, and prompt engineering over frontier models from Anthropic and OpenAI.\nYou'll work across the full stack: backend services in Python, Java, Node.js, or Go, and TypeScript/React frontends spanning both web and mobile app experiences. You'll make AI dependable by building automated evaluation pipelines, guardrails, and testing strategies for non-deterministic outputs - and running it on production infrastructure: scalable, fault-tolerant services on AWS and Kubernetes.\nYou'll think like a product engineer, not a ticket-taker: dig into user needs, absorb the problem space, make smart calls about what to build, keep stakeholders informed, and find ways to unblock yourself.\nThe Skills You’ll Have:\nFull-Stack Product Engineering\nBuild production backend services in one or more of Python (FastAPI or similar), Java, Node.js, or Go.\nShip production web interfaces in TypeScript and React; mobile app development (React Native or similar) is a plus.\nDesign REST APIs and data models across relational and NoSQL databases.\nOwn features end-to-end: implementation, testing, deployment, and monitoring.\nAI / LLM Engineering\nBuild with LLM APIs (Anthropic, OpenAI): agentic workflows, tool/function calling, RAG pipelines, and prompt engineering. Production experience preferred; substantial personal or open-source projects considered.\nWrite evaluation pipelines and testing strategies for non-deterministic AI outputs.\nBonus: agent frameworks (LangChain, LangGraph, LlamaIndex, CrewAI), Model Context Protocol (MCP), LLMOps tooling (LangSmith, Langfuse), vector databases, or model serving (vLLM, GPU inference).\nProduction Systems & AI Infrastructure\nDeploy and operate services on AWS with Docker, Kubernetes, and CI/CD (Scout runs on AWS).\nInstrument systems with observability and handle customer data securely in AI systems.\nDesign fault-tolerant, scalable services that serve AI workloads reliably.\nSalesforce platform and Apex - Scout integrates with the Sitetracker Salesforce platform.\nProduct Thinking & Communication\nDig into user needs and use that context to decide what to build and how.\nExplain technical decisions and AI concepts clearly to technical and non-technical audiences.\nBreak challenges into iterative solutions, keep stakeholders informed, and unblock myself.\nWithin 90 Days, You’ll:\nRamp up on Scout's architecture, codebase, and AI tooling.\nShip your first AI-driven product features with support from senior engineers.\nBuild a working knowledge of our evaluation pipelines and deployment workflow on AWS.\nWithin 180 Days, You’ll:\nIndependently deliver AI product features end-to-end, with increasing complexity.\nContribute to design discussions and team best practices for secure, scalable AI development.\nOwn the quality of your features in production: monitoring, evals, and iteration.\nWithin 365 Days, You’ll:\nConsistently deliver well-crafted, end-to-end AI product capabilities that increase velocity and throughput.\nElevate team quality through strong technical work, thoughtful code reviews, and knowledge sharing.\nServe as a go-to contributor for agentic systems on 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