Applied AI Engineer
About The Position
HireNow Staffing is actively recruiting multiple seasoned, highly skilled Applied AI Engineers to join one of our valued client partners. HireNow Staffing is acting as a direct placement partner for this Applied AI Engineering opportunity within the fintech and institutional investment technology sector. This position is built for engineers who thrive in fast-moving environments and enjoy building AI-powered applications that solve complex operational problems for institutional finance teams. The selected candidates will work on production-grade AI systems used by sophisticated investment organizations, transforming research, analytics, and operational workflows through modern AI infrastructure and automation. This is not a research-focused AI role. The client is seeking engineers who can build, deploy, and scale user-facing AI applications using modern LLM infrastructure, agentic frameworks, orchestration tooling, and full-stack engineering principles. Candidates must be comfortable operating in highly unstructured startup environments where ownership, execution speed, and technical depth are essential.
Requirements
- 3–8 years of experience as a Full-Stack Software Engineer or Applied AI Engineer
- Strong Python development expertise with production API experience using FastAPI, Flask, or Django
- Demonstrated experience building user-facing AI products from concept through deployment
- Hands-on experience integrating frontier LLM APIs such as Anthropic or OpenAI
- Proven experience using agentic AI tooling including MCP servers, Claude Code, Codex, LangGraph, OpenClaw, LangChain, OpenCode, or similar frameworks
- Strong understanding of agentic loop architecture, state handling, orchestration, and context management
- Experience building full-stack applications using React and backend API systems
- Comfortable operating within startup-style, highly unstructured environments
- Stable employment history with demonstrated ownership of long-term projects and product delivery
- Strong communication skills with ability to collaborate directly with technical and non-technical stakeholders
Nice To Haves
- Prior fintech, hedge fund, institutional investment, biotech, or quantitative systems experience
- Experience building AI-powered workflow automation tools or financial intelligence platforms
- Familiarity with Kubernetes deployments and cloud infrastructure environments
- Experience working with portfolio analytics, risk systems, or data-intensive applications
- Strong understanding of data orchestration and distributed system workflows
- Experience working within high-performance engineering teams delivering products rapidly
Responsibilities
- Build AI-powered client applications leveraging modern LLM infrastructure and orchestration frameworks
- Develop agentic workflows, automation layers, and intelligent research systems for institutional investment teams
- Design and maintain backend APIs using Python frameworks such as FastAPI, Flask, or Django
- Build responsive frontend applications using React and modern UI tooling
- Implement MCP-connected data sources, orchestration pipelines, and AI agent frameworks
- Develop ETL pipelines supporting portfolio analytics, securities data, research signals, and operational workflows
- Create scalable infrastructure supporting observability, orchestration, AI tooling, and workflow automation
- Work directly with client stakeholders to convert operational challenges into production-ready software solutions
- Support Kubernetes-based deployments across client environments
- Continuously iterate on AI products in compressed delivery cycles while maintaining production quality standards
Benefits
- Full benefits package available
- Equity participation available
- Visa sponsorship flexibility available for qualified candidates
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
