{"id":2047081,"url":"https://alion.io/job/built-in-applied-ai-engineer","title":"Applied AI Engineer","company":{"id":38558,"name":"Built In","domain":"builtinsf.com","url":"https://alion.io/company/builtinsf","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":".NET","optional":false},{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"C#","optional":false},{"name":"ChatGPT","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Function Calling","optional":false},{"name":"Gemini","optional":false},{"name":"Human-in-the-Loop","optional":false},{"name":"LLM","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"Perplexity","optional":false},{"name":"Python","optional":false},{"name":"Structured Outputs","optional":false}],"status":"live","first_seen_at":"2026-10-07T19:33:32Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-12T13:03:04Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Hello, We’re Built In\nWhat We’re Up To \nWe’re building the largest platform for tech professionals globally. Monthly, millions of professionals visit BuiltIn.com from across the world. We’re the only platform they need to stay ahead of tech trends and news, develop their careers and find opportunities at companies they believe in.\nOur 1,800 customers include innovative companies of all sizes, from exciting startups to companies in the Fortune 100. To attract our audience of skilled professionals, they trust us to tell the stories of their cultures and share their job opportunities. This helps them hire the industry’s most sought-after professionals locally, nationally and remotely - ultimately contributing to the industry’s ability to innovate a better future.\nWhat You’ll Be a Part Of Working at Built In is the chance to help shape a fast-growing company. With venture funding of $30 million to date, we’re expanding not just our geographic footprint but our products and technology. You’ll also be a part of changing the lives of professionals like you, ambitious people with a passion for tech and love of learning. As a result, you’ll understand the impact of your work in a deeply personal, especially meaningful way.\nAbout the Role\nWe are looking for an Applied AI Engineer to design and build the autonomous systems that power Built In’s product suite. Our platform already generates deep analytical insights for customers-your job is to build the Agentic Action Layer that turns those insights into outcomes. You will create multi-agent systems that don’t just surface data but take intelligent, supervised action across the major AI frontiers: ChatGPT, Google Gemini, and Perplexity.\nThe ideal candidate has already shipped production agentic systems and knows where orchestration frameworks help versus where they get in the way. You operate with a human-in-the-loop mindset, using agentic tooling to compress what would traditionally be a team-sized effort into individual throughput-without sacrificing reliability.\nHow You’ll Contribute\nArchitect Agentic Systems: Design and implement production-grade agentic workflows-including Reflection, Self-Correction, Planning, and Multi-Agent Orchestration patterns-to power a growing portfolio of AI-driven product capabilities.\nOperationalize Agents in Production: Own the full lifecycle from rapid prototype to production deployment. Build agent systems with real-world constraints in mind: token budgets, latency targets, graceful degradation, and cost observability.\nEvolve Multi-Model Intelligence: Develop systems that synthesize outputs from ChatGPT, Gemini, and Perplexity to identify sentiment discrepancies, detect brand hallucinations, and surface actionable intelligence for customers.\nBuild Scalable Cloud Infrastructure: Design and maintain serverless backend services using Python and AWS Lambda, ensuring agents perform efficiently at scale with proper observability.\nDrive Evaluation and Quality: Build LLM-as-a-Judge evaluation frameworks, trace-based testing pipelines, and quality feedback loops that keep agent output reliable as models and prompts evolve.\nCollaborate Across Teams: Work closely with Software Engineers and Product Managers to integrate agentic behaviors into production frameworks, ensuring AI systems are stateful, observable, and resilient.\nWhat You Bring\nDeep experience designing and shipping autonomous systems using patterns like ReAct, Planning, Reflection, and Multi-Agent Orchestration. You’ve moved agents from demo to production and dealt with the hard parts: failure handling, state management, and non-deterministic outputs.\nExpert-level implementation experience with frontier model APIs from OpenAI, Google, and Perplexity, including function calling, structured outputs, and streaming.\nYou are a power user of agentic developer tools (e.g., Claude Code, Cursor, or custom agentic CLI workflows). You use these to architect, refactor, test, and ship-not just autocomplete.\nDemonstrated ability to manage multiple autonomous agents across a codebase: writing, testing, and auditing code with minimal manual intervention.\nStrong proficiency in Python for AI orchestration, plus working knowledge of C# / .NET. Our core platform runs on .NET, and you’ll need to integrate your agent systems with it-not just work alongside it.\nPractical experience deploying and operating serverless architectures on AWS (Lambda, Step Functions, EventBridge) for high-frequency, agentic workloads.\nExperience building custom evaluation frameworks (LLM-as-a-Judge, trace-based testing, regression suites) to maintain and improve agent output quality over time. You understand that the hardest part of production agents isn’t building them-it’s knowing when they’re wrong.\nWhat We Value\nWe’re revolutionizing tech recruitment. So we question everything, because the best answers sit just to the right of a question mark. If you join Built In, you will work from this set of values:\nBe Inclusive, Always. * Be Unreasonably Passionate. * Be Humble. * Stay Curious. * Lead with Solutions. * Own the Result. * Do More. ---\nBe Inclusive, Always\nResearch shows that women and other marginalized groups tend to apply to roles only when they check every point on a job description. We encourage you to apply if you meet the majority of qualifications and this role is aligned with your career trajectory.\nBuilt In is an equal employment opportunity employer. Qualified candidates are considered for employment without regard to race, religion, gender, gender identity, sexual orientation, national origin, age, military or veteran status, disability, or any other characteristic protected by applicable law.\nBuilt In is guided by principles of diversity, equity and inclusion (DEI). We are committed to this work over the long-term, but here’s some of what’s in place today:\nWe have five thriving ERG groups: Built In For The People, BuiltOut, United We Parent, Women United in Tech and Built In Tribe.\nWe have a dedicated Director, HR + Inclusion who oversees our DEI roadmap.\nWe are proud to be led by a woman CEO and founder, and that more than half of our managers and employees identify as women.\nNOTE: BUILT IN NEVER CONTACTS JOB APPLICANTS VIA TEXT, MESSENGER OR OTHER SIMILAR APPLICATIONS. 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