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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and building AI-powered features and workflows, with a strong focus on LLM frameworks such as LangChain and LangGraph. Proven ability to mentor engineers and drive technical direction in AI workstreams while ensuring system reliability and effective integration across teams.
Highest-signal resume keywords
LLM Frameworks (LangChain, LangGraph)TypeScript / Node.js Backend DevelopmentAI System Reliability PracticesCloud Experience (AWS)Mentoring and Coaching Engineers
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 EngineeringLLM-Powered Features DevelopmentAgentic Systems BuildingPrompt EngineeringAPI DesignDatabase Proficiency (SQL/Postgres, NoSQL)Evaluation Frameworks for LLM OutputsEvent-Driven SystemsMulti-Step ReasoningHuman-in-the-Loop Patterns
Soft Skills
MentoringCoachingCollaborationInfluencing
Tools & Technologies
AWS (Lambda, ECS, S3)AI Coding Assistants (Copilot, Cursor, Claude)TerraformKubernetesDatadog
Industry Keywords
BlockchainCryptocurrencyComplianceRAGVector DatabasesMulti-Agent SystemsLLM Observability Tools
Tech Stack
Tools & technologiesAWSCloudJavaScriptKubernetesNode.jsNoSQLPostgresSQLTerraformTypeScript
About the role
Key responsibilities & impact- Design and build agentic workflows and AI-powered features for Elliptic's copilot using frameworks such as LangChain or LangGraph
- Lead the design of agents, tool integrations, and retrieval pipelines for complex blockchain data
- Build and own evaluation frameworks measuring LLM output quality, reliability, and latency
- Design and build backend services, APIs, and event-driven systems using TypeScript and Node.js
- Drive technical design reviews and architecture decisions for AI workstreams
- Mentor and coach junior engineers through pairing, code review, and design feedback
- Promote testing, observability, and AI system reliability practices
- Influence cross-team integration of AI capabilities across the Elliptic platform
- Ship significant AI capabilities end-to-end and drive AI workstream technical direction
- Build relationships across product, web engineering, data engineering, and DevOps
Requirements
What you’ll need- 5-8+ years of software engineering experience
- At least 1-2 years of meaningful production work building LLM-powered features
- Direct experience with LLM frameworks such as LangChain, LangGraph, or similar
- Hands-on experience building agentic systems, including tool use, multi-step reasoning, planning, memory, and human-in-the-loop patterns
- Practical understanding of prompt engineering, structured outputs, context management, and LLM trade-offs
- Experience building and running evaluations for LLM outputs
- Strong backend skills in TypeScript / Node.js and solid API design
- Cloud experience with AWS, including Lambda, ECS, S3, or similar
- Database proficiency across SQL/Postgres and some NoSQL exposure
- Demonstrated ability to mentor and coach other engineers
- Effective use of AI coding assistants such as Copilot, Cursor, or Claude
- Bonus: experience with RAG, vector databases, multi-agent systems, LLM observability tools, multiple model providers or fine-tuning, Terraform, Kubernetes, Datadog, SNS, SQS, cryptocurrency, blockchain, or compliance
Benefits
Comp & perks- Hybrid working and the option to work from almost anywhere for up to 90 days per year
- £500 Remote working budget to set up your home office space
- $1,000 Learning & Development budget
- 25 days of annual leave + bank holidays
- An extra day for your birthday
- Enhanced parental leave: 16 weeks fully-paid leave for eligible employees
- Private Health Insurance through Bupa
- Full access to Spill Mental Health Support
- Life Assurance covering 4 times your salary for beneficiaries
- Cycle to Work Scheme