{"id":3424306,"url":"https://alion.io/job/true-talent-solutions-partners-applied-ai-engineer-3","title":"Applied AI Engineer","company":{"id":4415660,"name":"True Talent Solutions Partners","domain":"truetalentsolutionspartners.com","url":"https://alion.io/company/true-talent-solutions-partners","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":200000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Django","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-10-28T17:42:37Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-30T17:06:44Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About the Role\nJoin a team building AI infrastructure and custom software for institutional finance. You will work with investment teams to turn complex research and analytics workflows into production-ready applications, using agentic AI to make financial work faster and more accessible.\nWhat You'll Do\nBuild user-facing LLM features such as research intelligence, natural-language querying, automated summaries, and agentic workflows.\n\nDevelop agent orchestration, MCP-connected data sources, and integrations using modern AI frameworks and tools.\n\nBuild full-stack applications for portfolio analytics, risk management, and investment research, from backend APIs to responsive interfaces.\n\nDesign and maintain Python APIs and reliable ETL pipelines for positions, securities, risk metrics, and research data.\n\nImplement financial analytics and performance or risk calculations using time-series and linear algebra tools.\n\nDeploy and iterate on production software, incorporating direct user feedback while balancing speed and quality.\n\nWhat We're Looking For\nThree to eight years of experience building applied AI products, including user-facing agentic features from initial concept to launch.\n\nStrong first-principles understanding of agentic workflows and a track record of using AI development tools effectively.\n\nProficiency in Python and API development with FastAPI, Flask, or Django, plus experience with React, SQL, and cloud or AI infrastructure.\n\nHands-on experience with LLM APIs, MCP servers, agent frameworks such as LangChain, and prompt engineering.\n\nExperience building applications on existing AI infrastructure, rather than focusing primarily on model training or research.\n\nInterest or experience in institutional finance, fintech, quantitative work, or other data-intensive fields, with curiosity about how investment teams make decisions.\n\nComfort working in unstructured environments, solving loosely defined problems, and delivering user-facing software.\n\nCompensation & Benefits\nBase salary: $200,000 to $250,000 USD annually. 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