FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Python and experience in building production agent systems, with a strong focus on architectural design and evaluation methodologies for AI systems. Capable of effectively communicating technical concepts to stakeholders and collaborating with customer engineering teams throughout the Agent Development Lifecycle.
Highest-signal resume keywords
Python ProgrammingAgent Development Lifecycle (ADLC)LangChain/LangGraph/Deep AgentsEvaluation Methodologies for AI SystemsClient-Facing Communication Skills
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringProduction Agent SystemsArchitectural DesignEvaluation MethodologiesTrace MiningDataset CurationPost-Training TechniquesMulti-Agent PatternsState ManagementFine-Tuning
Soft Skills
Strong Communication SkillsClient EngagementAdvisory Skills
Tools & Technologies
AxolotlUnslothHugging Face TransformersTRL
Industry Keywords
Enterprise WorkflowsCustomer Agent ArchitecturesProduction DeploymentOrchestration PatternsCustom Conversational UIs
Tech Stack
Tools & technologiesJavaScriptPythonTypeScript
About the role
Key responsibilities & impact- Translate vague enterprise workflows into concrete software specifications
- Guide engineering teams through resulting solutions or build solutions for customers
- Design customer agent architectures
- Co-build evaluation pipelines with customer engineering teams
- Embed within customer teams for extended engagements and ship agent systems directly
- Advise on agent architecture design, evaluation strategy, and production best practices
- Co-build with customer engineering teams across the full Agent Development Lifecycle (ADLC)
- Deliver agent engineering across architecture design, orchestration patterns, evaluations, custom conversational UIs, and production deployment
- Apply post-training, supervised fine-tuning, harness engineering, trace mining, model selection, and evaluation methodology
- Work directly with enterprise customers to build reliable, production agents
Requirements
What you’ll need- 4+ years of software engineering experience with deep expertise in Python
- TypeScript/JavaScript a plus
- 2+ years of hands-on experience building and shipping production agent systems
- Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs)
- Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory)
- Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems
- Comfortable operating across the full spectrum from advisory to embedded delivery
- Willing to travel up to 20% of the time
- Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL
- Experience with trace mining to drive continuous improvement loops
- Ability to submit a portfolio
Benefits
Comp & perks- Competitive compensation including base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks
- Locally competitive benefits aligned with regional norms and regulations for team members in the EU, UK, and APAC
- Medical coverage
- Dental coverage
- Vision coverage
- Flexible vacation
- 401(k) plan
- Meals on in-office days in the US