Mid Level AI Research Engineer Jobs
Mid level ai research engineer jobs go to researchers ready to own projects end to end, drive model design decisions with limited oversight, and mentor junior teammates on methodology and best practices. Hiring runs heavily remote and hybrid across Technology & Software, Education, and Science & Research, with employers like Bosch, TikTok, and DoorDash competing for engineers at this level now.
Find JobsOverview
Showing 5 of 46+ Mid Level AI Research Engineer jobs
Job Title: AI Coding Tools Engineer (Sr. AI Full-Stack Engineer with Coding Tools [Claude Code, Codex] and agentic AI)
Location: Chantilly, VA
Notes
- Windows and Linux experience (ideally Admin experience) and capable of configuring different coding tools in internal hosted Windows and Linux environments.
- Project management and communications skills to be able to manage different projects and communicate with different parties, with the client, for supporting the operation and roll-out of a variety of coding assistant tools.
- Familiarity with some of the existing coding assistant tools (e.g., Claude Code, Cline, Codex).
Position Description: AI Coding Tools Engineer
The AI Coding Tools Engineer (GenAI & Agentic Systems) evaluates, pilots, operationalizes, maintains, and scales adoption of secure AI coding assistant tools across the enterprise.
Key Responsibilities
AI Coding Assistant Evaluation
- Conduct structured evaluations of leading enterprise AI coding assistants, including features, model performance, security, integration complexity, and developer ergonomics.
AI Coding Assistant Piloting, Launching & Adoption Support
- Integrate coding assistants into IDEs (VS Code), terminals/CLI workflows, and source-control ecosystems.
- Configure AI guardrails, including content filtering, prompt-shielding, and role-based access controls aligned with enterprise and NIST requirements.
- Work with Security Team to prepare ATO evidence, including SSP updates, control narratives, risk registers, and continuous-monitoring artifacts.
- Work with Training and Enablement Team to develop training, compliance, and end-user/best-practice guides.
- Support Coding Assistant “office hours” to support developer enablement and accelerate adoption.
- Collect user feedback, track adoption metrics, and iteratively refine usage patterns for different developer roles.
AI Coding Assistant Operations & Maintenance Support
- Monitor platform health and guardrail performance.
- Support analysis and remediation of integration or platform issues impacting the coding assistants.
- Track, evaluate, and support application of coding assistant updates and patches.
Required Qualifications
- Minimum 2 years of experience with leading AI Coding Assistants.
- Minimum 3–5 years of experience in software engineering, developer experience engineering, platform engineering, or related roles.
- Experience integrating or evaluating LLM-powered developer tools (e.g., code completion, chat-based programming assistance, test generation, refactoring tools).
- Understanding of NIST compliance and government cloud environments.
- Familiarity with enterprise DevSecOps practices, modern IDEs, and secure software development lifecycles.
Preferred Qualifications
- Direct experience leading enterprise adoption of AI coding assistants (pilot design, rollout planning, governance alignment).
- Hands-on experience with Amazon Bedrock GovCloud, Azure OpenAI (Gov), and/or Vertex AI (Assured Workloads) for production workloads.
- Experience building multi-step agent workflows on Bedrock Agents, implementing Bedrock Guardrails, or building RAG/semantic-search systems via Vertex AI Search.
- Experience supporting ATO artifacts and design/testing of controls.
Job Title: AI Coding Tools Engineer (Sr. AI Full-Stack Engineer with Coding Tools [Claude Code, Codex] and agentic AI)
Location: Chantilly, VA
Notes
- Windows and Linux experience (ideally Admin experience) and capable of configuring different coding tools in internal hosted Windows and Linux environments.
- Project management and communications skills to be able to manage different projects and communicate with different parties, with the client, for supporting the operation and roll-out of a variety of coding assistant tools.
- Familiarity with some of the existing coding assistant tools (e.g., Claude Code, Cline, Codex).
Position Description: AI Coding Tools Engineer
The AI Coding Tools Engineer (GenAI & Agentic Systems) evaluates, pilots, operationalizes, maintains, and scales adoption of secure AI coding assistant tools across the enterprise.
Key Responsibilities
AI Coding Assistant Evaluation
- Conduct structured evaluations of leading enterprise AI coding assistants, including features, model performance, security, integration complexity, and developer ergonomics.
AI Coding Assistant Piloting, Launching & Adoption Support
- Integrate coding assistants into IDEs (VS Code), terminals/CLI workflows, and source-control ecosystems.
- Configure AI guardrails, including content filtering, prompt-shielding, and role-based access controls aligned with enterprise and NIST requirements.
- Work with Security Team to prepare ATO evidence, including SSP updates, control narratives, risk registers, and continuous-monitoring artifacts.
- Work with Training and Enablement Team to develop training, compliance, and end-user/best-practice guides.
- Support Coding Assistant “office hours” to support developer enablement and accelerate adoption.
- Collect user feedback, track adoption metrics, and iteratively refine usage patterns for different developer roles.
AI Coding Assistant Operations & Maintenance Support
- Monitor platform health and guardrail performance.
- Support analysis and remediation of integration or platform issues impacting the coding assistants.
- Track, evaluate, and support application of coding assistant updates and patches.
Required Qualifications
- Minimum 2 years of experience with leading AI Coding Assistants.
- Minimum 3–5 years of experience in software engineering, developer experience engineering, platform engineering, or related roles.
- Experience integrating or evaluating LLM-powered developer tools (e.g., code completion, chat-based programming assistance, test generation, refactoring tools).
- Understanding of NIST compliance and government cloud environments.
- Familiarity with enterprise DevSecOps practices, modern IDEs, and secure software development lifecycles.
Preferred Qualifications
- Direct experience leading enterprise adoption of AI coding assistants (pilot design, rollout planning, governance alignment).
- Hands-on experience with Amazon Bedrock GovCloud, Azure OpenAI (Gov), and/or Vertex AI (Assured Workloads) for production workloads.
- Experience building multi-step agent workflows on Bedrock Agents, implementing Bedrock Guardrails, or building RAG/semantic-search systems via Vertex AI Search.
- Experience supporting ATO artifacts and design/testing of controls.
See All 46 Mid Level AI Research Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsMid Level AI Research Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software21
- Education4
- Science & Research4
- Banking & Financial Services4
- Manufacturing3
Mid Level AI Research Engineer Jobs: Frequently Asked Questions
How do I get a mid level ai research engineer job?
Position your work by leading with concrete outcomes: models you shipped, benchmarks you moved, and research problems you scoped independently. Hiring managers at this level look for evidence of ownership, not just contribution. Highlight any cross-functional work, publications, or internal tools you drove from idea to deployment. A focused portfolio with two or three strong projects carries more weight than a broad list of tasks.
Which companies hire mid level ai research engineers?
Companies hiring mid level ai research engineers right now include Bosch, TikTok, and DoorDash, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes from a mix of large technology companies running dedicated research teams, well-funded AI startups scaling their core modeling work, and enterprise organizations building applied research functions.
Are there remote mid level ai research engineer jobs?
Yes, remote availability at this level is strong. About 24% of mid level ai research engineer openings are remote or hybrid as of September 2026, reflecting the nature of deep-focus research work that translates well to distributed settings. Many teams hiring at this level have established async workflows and expect candidates to be comfortable working independently across time zones.
How do I move up to a mid level ai research engineer role?
Moving into a mid level ai research engineer role typically follows a path of deepening specialization and accumulating ownership. Early in your career, focus on mastering a core area such as NLP, computer vision, or reinforcement learning rather than staying generalist. Over time, seek out opportunities to lead a research workstream, reproduce and extend published work, and document results clearly. Measurable impact on a real system is what signals readiness for mid level responsibilities.
Which industries hire the most mid level ai research engineers?
Mid Level ai research engineer roles concentrate in Technology & Software, Education, and Science & Research, based on current listings on Migrate Mate as of September 2026. These sectors invest heavily in proprietary model development and need researchers who can move from proof of concept to production without close supervision.