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From Home Applied Engineer Jobs (NOW HIRING)

Microsoft

Applied Engineer II

Redmond, WA

$133K - $219K/yr

Overview As an Applied Engineer II you will play a pivotal role in contributing to the development ... from ideation to shipping. Software Engineering IC3 - The typical base pay range for this role ...

Deepgram

Senior Solutions Engineer, Federal

Washington, DC · Remote

$62.50 - $80.75/hr

We measure how effectively AI is applied to deliver results, and consistent, creative use of the ... You will own the full technical lifecycle of federal engagements, from initial discovery and proof ...

Applied Engineering

Process Engineer

Oshkosh, WI · On-site

$97K - $112K/yr

With support from our team across Wisconsin, we welcome candidates from Ripon, Appleton, Osh Kosh ... Collaborate with suppliers and Applied partners across northern Wisconsin to strengthen ...

Applied Engineering

Process Engineer

Fond Du Lac, WI

$97K - $112K/yr

With support from our team across Wisconsin, we welcome candidates from Ripon, Appleton, Osh Kosh ... Collaborate with suppliers and Applied partners across northern Wisconsin to strengthen ...

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Infographic showing various From Home Applied Engineer job openings in the United States as of June 2026, with employment types broken down into 1% Locum Tenens, and 99% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Applied Engineer

Steel Point Opportunities

New York, NY

Full-time

Posted 12 days ago

Job description

This role sits at the intersection of AI implementation and financial software. You won't just use AI tools you'll build AI-powered features directly into client platforms: LLM-driven research intelligence, agentic workflows, MCP-connected data sources, and automation layers that compress weeks of analyst work into seconds. The ideal candidate is a strong full-stack engineer who is fluent in modern AI tooling and deeply curious about how hedge funds and asset managers think, invest, and operate. Speed is a core part of the job the company delivers fully customized platforms in weeks, not months. What You'll Do: -AI-Powered Feature Development: Build LLM-powered features into client-facing platforms research intelligence tools, natural language query layers, automated summarization, and agentic workflows that change how investment teams work. -Agentic Tooling & MCP Integration: Design and implement MCP-connected data sources, agentic pipelines, and AI orchestration layers using frameworks like Claude Code, LangGraph, OpenClaw, OpenCode, and similar. -Full-Stack Application Development: Build end-to-end applications tailored to each client's unique portfolio analytics, risk management, and research workflows from backend APIs to responsive frontends. -Backend Services: Design and maintain high-performance APIs using Python (FastAPI or similar) powering client-specific data access, analytics, and AI inference. -Frontend Development: Build intuitive, responsive UIs in React enabling investment teams to interact with complex financial data clearly and efficiently. -Data Pipeline Development: Build and maintain ETL pipelines handling positions, securities, risk metrics, and research signals with reliability and performance. -Financial Analytics: Implement analytics layers for performance and risk calculations using timeseries and linear algebra operations (Pandas, Polars). Ship Fast, Iterate Often: Deliver working software in compressed timelines, gather direct user feedback, and continuously improve treating speed and quality as complementary. -Kubernetes Deployments: Work fluidly with Kubernetes within each client environment to ship fast and reliably. What Required to Succeed: -3 8 years as a full-stack SWE or applied AI engineer (institutional investor or fintech) -Demonstrated record using agentic AI tooling effectively (Claude Code, Codex, MCP servers) and building user-facing products 0-to-1 -Strong Python expertise (non-negotiable; API experience with FastAPI, Flask, or Django highly preferred) -First-principles understanding of the agentic loop used within most agentic frameworks (Codex, Claude Code, OpenCode, Cline, etc.) -Effective in unstructured environments and ability to solve loosely defined problems -Genuine conviction that AI is transforming software and deep interest in how institutional investors think and use tech Company Preferences: -Institutional investor or fintech experience (Two Sigma, DE Shaw, Citadel, P72, Addepar) or other data-first/quantitative fields (health/biotech) -AI implementation experience hands-on building with LLM APIs, MCP servers, agentic frameworks (Claude Code, OpenClaw, LangChain), prompt engineering, etc.

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