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.
Responsibilities
- Design 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 decisions
- Develop production LLM applications on Anthropic and OpenAI SDKs, including prompt engineering, structured outputs, tool/function calling, prompt caching, and batch processing
- Build and maintain RAG pipelines — embedding generation, vector/hybrid search, knowledge base ingestion — and apply judgment about when retrieval actually helps versus adds noise
- Own 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 equivalent
- Drive cost and latency optimization — token budgets, model tier selection (Haiku / Sonnet / Opus and GPT equivalents), and caching strategies that hold up at scale
- Build 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 more
- Implement and maintain production integrations using REST, GraphQL, webhooks, and event-driven patterns (queues, Pub/Sub) with proper idempotency, retry logic, and backfill support
- Wire up OAuth/SAML authentication flows (Okta in particular) for secure agent-to-service access across internal and third-party systems
- Own cloud infrastructure for AI workloads on GCP using Terraform, GKE/Cloud Run, and secrets management — with logging, metrics, and alerting from day one
- Build data pipelines that feed AI systems: strong SQL, Athena/BigQuery-class warehouses, ETL/ELT, schema design, and data-quality monitoring
- Partner with internal teams across Engineering, Operations, Customer Support, Data, and Finance to identify where agentic automation can have the highest leverage — then build it
- Create reusable libraries, SDKs, and internal tooling so teams can extend AI capabilities without starting from scratch
- Act as a technical advisor and embedded engineer, translating ambiguous business problems into well-scoped AI systems with clear success metrics
- Instrument and monitor deployed agents in production — you’re on-call for what you ship, and you treat reliability as a feature
Skills
- 5+ years of production software engineering experience, primarily in Python or TypeScript. Go is a plus
- Production LLM application experience with Anthropic or OpenAI SDKs — agents, structured outputs, tool use, RAG, evals, batch processing — shipped, not demoed
- Forward-deployed instinct: engineering, developer relations, or solutions engineering experience
- Strong evaluation discipline with the ability to define and defend exit criteria using LangSmith, Braintrust, or equivalent tools
- Experience building multi-step tool-using agents with planning, error recovery, and human-in-the-loop design in production environments
- Experience with RAG pipelines, embeddings, hybrid search, and the judgment to determine when retrieval improves outcomes
- Experience building MCP servers, function-calling schemas, and sandboxed execution environments
- Strong understanding of token budgets, model tier trade-offs, and AI cost/latency optimization strategies
- Experience integrating REST APIs, GraphQL, webhooks, OAuth/SAML authentication (especially Okta), and event-driven architectures
- Cloud-native engineering experience with GCP or AWS, including Terraform, containers, secrets management, logging, metrics, and alerting
- Strong SQL and data engineering experience with modern warehouses, ETL/ELT pipelines, schema design, and data-quality monitoring
- Ability to work cross-functionally and translate ambiguous business problems into production-ready AI systems
- Strong communication skills with both technical and non-technical stakeholders
- Trading industry, fintech, or capital markets experience
- Futures trading knowledge
- Experience with LangChain, LlamaIndex, or similar orchestration frameworks
- Familiarity with observability tooling such as OpenTelemetry, Prometheus, and Grafana
- Contributions to open-source AI or developer tooling projects
Benefits
- Annual 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 contributions
- Annual paid time off allowance accrues at a rate of 18 days per year (some positions may qualify for more) plus seven paid holidays
- For Chicago-based employees, we follow a hybrid work schedule: In-office Tuesday through Thursday, with remote work on Mondays and Fridays
- 20 additional flex remote days annually
- 5 Company Wide Office-Optional weeks tied to major holidays
- Generous PTO
- 7 Paid Holidays Annually + 5 Conditional Holidays Annually
- 1 Service Day Annually
- 401k with 3.5% Company Match
- Paid Parental Bonding Leave
- Health, Vision, Dental Coverage
- Life and Disability Insurance Covered 100% by NinjaTrader
Company Overview
NinjaTrader 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.