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Full Stack Ai Engineer Jobs in Missouri (NOW HIRING)

We are looking for a Senior Software Engineer Full Stack who will be required to solve critical problems for Global Integrated Fulfillment application Production Support function. This Global ...

AI Solutions Engineering Delivery Lead

Kansas City, MO ยท On-site

$100K - $131K/yr

... full-stack AI solutions. As a senior technical leader, you will leverage deep technical ... Data Science, Engineering, Mathematics, or related technical field - Minimum of 10 years of ...

AI Solutions Engineering Delivery Lead

Saint Louis, MO ยท On-site

$99K - $131K/yr

... full-stack AI solutions. As a senior technical leader, you will leverage deep technical ... Data Science, Engineering, Mathematics, or related technical field - Minimum of 10 years of ...

... engineering experience * Have built mobile apps (and/or web apps) full-stack before ... Enthusiastic about photo sharing and/or AI and/or social media

Showing results 41-60

Full Stack Ai Engineer information

See Missouri salary details

$41.7K

$126.4K

$178.7K

How much do full stack ai engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for full stack ai engineer in Missouri is $126,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,100.00 and $148,200.00 per year, depending on experience, location, and employer.

What is a full stack AI engineer?

A Full Stack AI Engineer is a professional who develops and deploys artificial intelligence solutions across both the front-end and back-end of applications. They combine expertise in AI and machine learning with software engineering skills, allowing them to build, integrate, and maintain AI-powered features throughout the entire technology stack. Their responsibilities often include designing machine learning models, integrating them with APIs, and ensuring seamless user experiences on web or mobile platforms. Full Stack AI Engineers bridge the gap between data science and software development, enabling scalable and production-ready AI applications.

How do full stack AI engineers typically collaborate with data scientists and front-end developers on AI-driven projects?

Full Stack AI Engineers often serve as the bridge between data scientists, who develop machine learning models, and front-end developers, who build user interfaces. They work closely with data scientists to understand the model requirements and deployment needs, and with front-end teams to ensure seamless integration of AI functionalities into applications. This collaboration requires effective communication skills and a clear understanding of both the technical and user experience aspects. Regular meetings, code reviews, and shared documentation are common practices to facilitate smooth teamwork and successful project outcomes.

What are the key skills and qualifications needed to thrive as a full stack AI engineer?

To thrive as a Full Stack AI Engineer, you need strong programming skills (such as Python, JavaScript), understanding of machine learning algorithms, and experience with both front-end and back-end development, often supported by a degree in computer science or related fields. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, Azure, GCP), and containerization tools (Docker, Kubernetes) is typically required. Excellent problem-solving abilities, collaboration, and effective communication are standout soft skills in this role. These skills and qualifications enable the seamless integration of AI models into scalable applications, ensuring innovative and robust solutions.
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Infographic showing various Full Stack Ai Engineer job openings in Missouri as of August 2026, with employment types broken down into 76% Full Time, 19% Part Time, and 5% Contract. Highlights an 67% Physical, 3% Hybrid, and 30% Remote job distribution, with an average salary of $126,415 per year, or $60.8 per hour.

Senior Software Engineer, Full Stack - Agentic AI

Socket.dev

California, MO โ€ข On-site

$170 - $220/hr

Other

Posted 3 days ago

New


Job description

About Sift

Sift is the data infrastructure platform for hardware engineering teams. Sift turns high-frequency telemetry into engineering insights for mission-critical systems. Teams use Sift to build and operate rockets, satellites, autonomous vehicles, energy systems, defense platforms, and more.Founded by former SpaceX engineers who built the tools behind Dragon and Starlink, Sift is building the data infrastructure to herald the AI era for physical systems.

About the Role

Hardware programs generate far more telemetry than any team can review by hand. Sift Agents is our answer: AI agents that work alongside hardware engineers, investigating anomalies, reviewing test and flight data, and answering in minutes questions that used to take a day of scripting.

This role comes with real product ownership and autonomy. You will talk directly to customers to understand how they review their machines, decide what to build, and own it from first MVP through every iteration after it ships. The surface area is wide: one day you might be polishing the frontend micro-interactions that make the chat experience feel great, the next you might be writing the Kubernetes scaling logic that orchestrates agent workloads. Weโ€™re heavy users of frontier agentic products ourselves and have strong opinions about what makes them great. Sift Agents is where we put those opinions to work.

This is a product engineering role, not a research role. Most of the work is the hard part of making agents dependable: tool design, context management, code execution environments, evaluation, and observability.

In This Role, Youโ€™ll:

  • Talk directly to customers and partner with product to turn real review workflows into agent capabilities: generating dashboards, writing analysis scripts, and surfacing insights buried in their telemetry

  • Design, ship, and operate agentic systems that reason over large-scale time-series data and hardware domain context

  • Build everything around the model that makes agents dependable: tool interfaces, sandboxed execution for agent-generated code, context and memory management, custom compaction algorithms, opinionated skills, and guardrails

  • Develop and maintain Siftโ€™s MCP server, the tool surface that lets both our agents and our customersโ€™ AI tools query telemetry directly

  • Work across the whole stack

    • Build the frontend surfaces where Sift Agents live, and make them feel great

    • Design and implement the APIs that power our agentic capabilities

    • Run agents reliably at scale, both in the cloud and on-prem

  • Build evaluation suites that measure whether agents actually help engineers, and instrument quality, latency, cost, and failure modes in production

  • Integrate and assess frontier models across providers

The Skillset Youโ€™ll Bring:

  • Have 8+ years of professional software engineering experience

  • Get excited about owning a product area: talking to customers, deciding what to build, and shipping it

  • Have built frontend web applications with technologies like React, NextJS, or similar

  • Have built APIs (REST, gRPC, etc.) or backend services with technologies like Go, Python, Rust, or similar

  • Are curious about new AI products: you try new agents, models, and features as they ship, and have opinions about what makes them good

Bonus Points:

  • Shipped products to users at scale: large data volumes, significant active user counts, or deep technical complexity

  • Shipped LLMโ€‘powered features

  • Built agentic systems: multiโ€‘step tool use, planning loops, context management, and evals

  • Designed tool ecosystems for agents, including MCP

  • Worked with sandboxed or isolated execution of generated code

  • Operated services in production (Kubernetes, observability, incident response)

  • A personal ecosystem of AI dev tooling: custom agents, skills, scripts, or workflows built to ship faster

  • A background in time-series data, scientific computing, or hardware test and telemetry

  • Built internal agentic tooling that accelerates an engineering org

Engineering At SIFT:

Youโ€™ll have the opportunity to help evolve and scale our platform because weโ€™re still in the early stages of building the product. Relevant technologies include:

  • Web frontend & backend: ECharts, Go, gRPC, PostgreSQL, Protobuf, Radix, React, Redux, and TypeScript

  • Data: Arrow, DataFusion, Flink, Parquet, and Rust

  • Infrastructure: Argo CD, AWS, Docker, GitHub Actions, Grafana, Kubernetes, Kustomize, Linux, Prometheus, and Terragrunt

Location:

Siftโ€™s headquarters is in Marina Del Rey, CA (Next to LAX). We collaborate in person twice a weekโ€”on Mondays and Thursdaysโ€”and come together for a full week every two months. We are open to relocating candidates to LA or working from our San Francisco office for the right candidate.

Salary range: $170,000 - $220,000 per year. Plus equity and benefits.

Eligibility:

U.S. Person Required: Must be a U.S. citizen, lawful permanent resident, or protected individual such as an asylee or refugee in compliance with ITAR (International Traffic in Arms Regulations) / EAR (Export Administration Regulations) regulations.

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