[Remote] Sr. Software Engineer, AI

Note: The job is a remote job and is open to candidates in USA. NinjaTrader is an industry-leading trading platform and futures broker, empowering traders to take control of their financial destiny. They are seeking a Senior Software Engineer specializing in AI to enhance the adoption of agentic AI across various departments, focusing on developing AI infrastructure and automation solutions.ResponsibilitiesDesign and build multi-step agentic workflows in Python and TypeScript — planning loops, tool dispatch, error recovery, and explicit human-in-the-loop checkpoints for high-stakes decisionsDevelop production LLM applications on Anthropic and OpenAI SDKs, including prompt engineering, structured outputs, tool/function calling, prompt caching, and batch processingBuild and maintain RAG pipelines — embedding generation, vector/hybrid search, knowledge base ingestion — and apply judgment about when retrieval actually helps versus adds noiseOwn eval discipline end-to-end: define offline eval sets, run A/B experiments on model changes, build regression suites, and articulate 'good enough' exit criteria using LangSmith, Braintrust, or equivalentDrive cost and latency optimization — token budgets, model tier selection (Haiku / Sonnet / Opus and GPT equivalents), and caching strategies that hold up at scaleBuild MCP servers and function-calling connectors that give agents reliable, schema-governed access to internal tools, APIs, and data sources — Jira, CRM, Slack, internal services, and moreImplement and maintain production integrations using REST, GraphQL, webhooks, and event-driven patterns (queues, Pub/Sub) with proper idempotency, retry logic, and backfill supportWire up OAuth/SAML authentication flows (Okta in particular) for secure agent-to-service access across internal and third-party systemsOwn cloud infrastructure for AI workloads on GCP using Terraform, GKE/Cloud Run, and secrets management — with logging, metrics, and alerting from day oneBuild data pipelines that feed AI systems: strong SQL, Athena/BigQuery-class warehouses, ETL/ELT, schema design, and data-quality monitoringPartner with internal teams across Engineering, Operations, Customer Support, Data, and Finance to identify where agentic automation can have the highest leverage — then build itCreate reusable libraries, SDKs, and internal tooling so teams can extend AI capabilities without starting from scratchAct as a technical advisor and embedded engineer, translating ambiguous business problems into well-scoped AI systems with clear success metricsInstrument and monitor deployed agents in production — you’re on-call for what you ship, and you treat reliability as a featureSkills5+ years of production software engineering experience, primarily in Python or TypeScript. Go is a plusProduction LLM application experience with Anthropic or OpenAI SDKs — agents, structured outputs, tool use, RAG, evals, batch processing — shipped, not demoedForward-deployed instinct: engineering, developer relations, or solutions engineering experienceStrong evaluation discipline with the ability to define and defend exit criteria using LangSmith, Braintrust, or equivalent toolsExperience building multi-step tool-using agents with planning, error recovery, and human-in-the-loop design in production environmentsExperience with RAG pipelines, embeddings, hybrid search, and the judgment to determine when retrieval improves outcomesExperience building MCP servers, function-calling schemas, and sandboxed execution environmentsStrong understanding of token budgets, model tier trade-offs, and AI cost/latency optimization strategiesExperience integrating REST APIs, GraphQL, webhooks, OAuth/SAML authentication (especially Okta), and event-driven architecturesCloud-native engineering experience with GCP or AWS, including Terraform, containers, secrets management, logging, metrics, and alertingStrong SQL and data engineering experience with modern warehouses, ETL/ELT pipelines, schema design, and data-quality monitoringAbility to work cross-functionally and translate ambiguous business problems into production-ready AI systemsStrong communication skills with both technical and non-technical stakeholdersTrading industry, fintech, or capital markets experienceFutures trading knowledgeExperience with LangChain, LlamaIndex, or similar orchestration frameworksFamiliarity with observability tooling such as OpenTelemetry, Prometheus, and GrafanaContributions to open-source AI or developer tooling projectsBenefitsAnnual target bonus of 12%Bonus pay at NinjaTrader is based on individual performance (50%) as well as company/team performance (50%)401K plan through ADP under which the company will match up to 3.5% of employee contributionsAnnual paid time off allowance accrues at a rate of 18 days per year (some positions may qualify for more) plus seven paid holidaysFor Chicago-based employees, we follow a hybrid work schedule: In-office Tuesday through Thursday, with remote work on Mondays and Fridays20 additional flex remote days annually5 Company Wide Office-Optional weeks tied to major holidaysGenerous PTO7 Paid Holidays Annually + 5 Conditional Holidays Annually1 Service Day Annually401k with 3.5% Company MatchPaid Parental Bonding LeaveHealth, Vision, Dental CoverageLife and Disability Insurance Covered 100% by NinjaTraderCompany OverviewNinjaTrader provides trading software and brokerage services for futures, forex, and equities markets. It was founded in 2003, and is headquartered in Chicago, Illinois, USA, with a workforce of 201-500 employees. Its website is http://www.ninjatrader.com.