Senior AI-Native Developer Job at Thoth AI

Senior Software Engineer, AI Developer Tools

At Docker, we make app development easier so developers can focus on what matter...

Location

United States , Seattle

Salary:

184600.00 - 260700.00 USD / Year

Docker

Expiration Date

Until further notice

Requirements

6+ years building production-grade backend systems or developer-facing tools
Hands-on experience with AI/ML technologies such as practical production experience with LLM APIs (OpenAI, Anthropic, etc.), prompt engineering, or AI agent development
Proficiency in Go (preferred), Rust, Java, or Python with strong software engineering fundamentals
Experience designing and building distributed systems, microservices, or platform infrastructure
Strong understanding of cloud-native systems (AWS, GCP, or Azure), APIs, and data stores
Solid grasp of CI/CD, automated testing, code review practices, and modern development workflows
Product-minded approach to building developer tools with focus on user experience and measurable outcomes
Excellent communication skills in remote, asynchronous environments with ability to document technical decisions clearly
Ownership mentality with bias for action and iterative delivery
Comfortable working autonomously across distributed teams and navigating ambiguity

Job Responsibility

Build AI-Powered Developer Tools: Design, implement, and ship production-ready AI agents and tools that accelerate developer productivity such as code review and refactoring assistants, automated test generators, local environment setup tools, deployment pipeline diagnostic agents, and on-call assistance tools
Implement LLM Integrations: Build robust, production-grade integrations with LLM APIs (OpenAI, Anthropic, etc.) such as prompt engineering, response parsing, error handling, rate limiting, cost management, and performance optimization
Develop Agent Orchestration Systems: Create agent frameworks and orchestration systems that enable complex multi-step workflows, tool calling, context management, and agent-to-agent communication
Contribute to Platform Infrastructure: Build self-service platform capabilities that enable teams across Docker to rapidly deploy and operate their own AI developer tools such as deployment pipelines, observability integration, security controls, and operational tooling
Drive Adoption of AI-Native Development: Build tools and programs that accelerate adoption of AI developer tools such as Claude Code, Cursor, and Warp across Docker's engineering organization
Ensure Production Quality: Write well-tested code with strong test coverage (unit, integration, end-to-end)
establish monitoring, alerting, and operational excellence for AI systems
Collaborate Cross-Functionally: Partner with Principal Engineer on architecture, work with product and design teams on features and UX, and collaborate with platform teams (Infrastructure, Security, Data) on integrations
Participate in Operations: Take part in on-call rotation for AI developer tools
respond to incidents, debug production issues, and drive continuous improvement of system reliability

What we offer

Freedom & flexibility
fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup
we want you comfortable while you work
16 weeks of paid Parental leave
Technology stipend equivalent to $100 net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity

Fulltime

Senior AI Scientist (Agentic AI)

We are on a lookout for a hands-on Senior AI Scientist (Agentic AI) to join the ...

Location

Germany , Berlin

Salary:

Not provided

Delivery Hero

Expiration Date

Until further notice

Requirements

2+ years of experience in applied AI/ML engineering with real-world deployments
Strong Python skills and experience with frameworks like LangChain, LlamaIndex, or Haystack
Deep knowledge of RAG, LLM mechanics, prompt design, and chaining
Experience with vector databases (Pinecone, Weaviate, FAISS) and embedding models
You take ownership
You move fast but don't cut corners
You believe working code beats perfect plans

Job Responsibility

Architect and deploy agent-based systems using LangGraph, PydanticAI, LangChain, Google ADK, Claude SDK, or custom-built orchestration frameworks
Build and optimize RAG pipelines
Design self-evolving prompt systems and dynamic decision flows driven by LLMs
Develop APIs and services that let models talk to tools, data, and other systems
Monitor, evaluate, and automate model feedback loops using AI-based simulation and testing agents
Work cross-functionally with product and engineering teams to ship AI-native features

What we offer

Hybrid working model with 2 days per week in Berlin campus
27 days holiday with an extra day on 2nd and 3rd year of service
1.000 € Educational Budget
Language Courses
Parental Support
Access to Udemy Business platform
Health Checkups
Meditation
Gym & Bicycle Subsidy
Employee Share Purchase Plan

Fulltime

Senior AI Engineer

Location

Poland

Salary:

Not provided

hyperexponential

Expiration Date

Until further notice

Requirements

Built or significantly evolved AI-assisted engineering workflows that measurably accelerated delivery speed while maintaining production reliability
Delivered complex product features across unfamiliar codebases by rapidly understanding architecture, dependencies, and constraints
Architected scalable cloud infrastructure and CI/CD systems that enabled fast, reliable software delivery in production environments
Implemented automated testing, security, or quality systems that reduced operational risk while increasing development velocity
Evaluated and integrated modern AI development tooling, selecting pragmatic solutions that improved productivity and software quality
Partnered with product and design to shape requirements and influence what gets built, demonstrating strong judgement across trade-offs between speed, quality, and scope

Job Responsibility

Design and deliver complex product epics at 3–5x the velocity of baseline engineering teams, ensuring high-quality functionality reaches customers faster without compromising system integrity
Architect AI-assisted guardrails across the SDLC, including autonomous testing pipelines, AI-driven security reviews, and automated code quality agents that maintain stability while enabling rapid iteration
Use AI tools to rapidly map dependencies and navigate unfamiliar parts of the hx codebase, safely delivering cross-domain improvements without relying on traditional ownership boundaries
Build and evolve AI-native development workflows, integrating tooling across coding, testing, CI/CD, and deployment environments
Translate successful strike team practices into reusable patterns, tooling, and paved road workflows that scale across the wider engineering organisation
Work directly with product, design, and customers to shape what gets built, pushing back on scope, finding simpler solutions, and focusing engineering effort on the problems that matter most, with ownership defined by impact rather than title

What we offer

Share Options at a highly successful Series B company
25 days of non-working + 14 Polish bank holidays for B2B
£5,000 budget for Learning & Development
Mental Health Support and Therapy via Spectrum Life
Optional access to Healthcare package provided by Luxmed + Multisport (fully funded by yourself as B2B Contractor)
Top-spec laptop (MacOS or Windows)
Share Options at a highly successful Series B company for UoP
£5,000 budget for learning & development for UoP
26 days of holiday + 14 Polish bank holidays for UoP
Company pension for UoP

Fulltime

Senior AI Engineer

At hyperexponential (hx), we’re building the AI-powered platform that enables th...

Location

United Kingdom

Salary:

Not provided

hyperexponential

Expiration Date

Until further notice

Requirements

Built or significantly evolved AI-assisted engineering workflows that measurably accelerated delivery speed while maintaining production reliability
Delivered complex product features across unfamiliar codebases by rapidly understanding architecture, dependencies, and constraints
Architected scalable cloud infrastructure and CI/CD systems that enabled fast, reliable software delivery in production environments
Implemented automated testing, security, or quality systems that reduced operational risk while increasing development velocity
Evaluated and integrated modern AI development tooling, selecting pragmatic solutions that improved productivity and software quality
Partnered with product and design to shape requirements and influence what gets built, demonstrating strong judgement across trade-offs between speed, quality, and scope

Job Responsibility

Design and deliver complex product epics at 3–5x the velocity of baseline engineering teams, ensuring high-quality functionality reaches customers faster without compromising system integrity
Architect AI-assisted guardrails across the SDLC, including autonomous testing pipelines, AI-driven security reviews, and automated code quality agents that maintain stability while enabling rapid iteration
Use AI tools to rapidly map dependencies and navigate unfamiliar parts of the hx codebase, safely delivering cross-domain improvements without relying on traditional ownership boundaries
Build and evolve AI-native development workflows, integrating tooling across coding, testing, CI/CD, and deployment environments
Translate successful strike team practices into reusable patterns, tooling, and paved road workflows that scale across the wider engineering organisation
Work directly with product, design, and customers to shape what gets built, pushing back on scope, finding simpler solutions, and focusing engineering effort on the problems that matter most, with ownership defined by impact rather than title

What we offer

£5,000 training and conference budget
25 days of holiday plus 8 bank holidays
Company pension scheme via Penfold
Mental health support and therapy via Spectrum.life
Individual wellbeing allowance via Juno
Private healthcare insurance through AXA
Income protection and Life Insurance
Cycle to Work Scheme
Top-spec equipment (laptop, screens, adjustable desks, etc.)
Regular remote and in-person hackathons, lunch and learns, socials, and game nights

Fulltime

Senior AI Engineer

We are hiring a Senior AI Engineer to help shape our AI systems and technical di...

Location

United Kingdom , London

Salary:

80000.00 - 90000.00 GBP / Year

Xelix

Expiration Date

Until further notice

Requirements

5+ years building and deploying ML or AI systems, with significant experience in production environments
Strong system design skills, ability to design end-to-end AI systems and make sound architectural decisions
Deep AI expertise, strong experience with LLM systems (agents, tool use, evals) and/or traditional ML where appropriate
Pragmatism, ability to choose the right approach for the problem, balancing complexity, performance, and cost
Evaluation mindset, experience designing and using evals to drive system improvements
Engineering excellence, high standards for code quality, testing, and maintainability
Leadership & mentorship, experience guiding other engineers and influencing technical direction
AI-native workflow, strong ability to leverage AI-assisted development tools effectively and thoughtfully

Job Responsibility

Design and lead end-to-end AI systems, from problem framing through to production deployment and iteration
Architect complex agent-based workflows, tool ecosystems, and multi-step reasoning systems
Make decisions on model selection, fine-tuning, and when to use ML vs LLM vs hybrid approaches
Define evaluation frameworks, metrics, and feedback loops to ensure reliability and continuous improvement
Ensure systems are scalable, observable, and robust in real-world environments
Mentor other engineers, review designs, and raise the bar for engineering and AI practices across the team
Drive effective use of AI tooling within the team, improving productivity without compromising quality
Work closely with product and leadership to shape what we build and why

What we offer

Competitive salary of £80,000 to £90,000 depending on experience
27 days of annual leave (including 3 days Christmas closing) which increases up to 3 days based on tenure, with the option to roll over, buy or sell up to 3 days
Hybrid working with two days a week from our dog-friendly Hoxton office
On-site gym and cycle to work scheme
Employee discount at over 100 retailers
Comprehensive private medical & dental cover with Vitality
Enhanced parental leave pay
Learning & development culture – £1,000 personal annual budget
We’re carbon-neutral and are working towards ambitious carbon reduction goals
Lots of team socials & activities

Fulltime

Senior AI Engineer

At Xelix, we work with some of the world’s largest companies to automate and str...

Location

United Kingdom , London

Salary:

80000.00 - 90000.00 GBP / Year

Xelix

Expiration Date

Until further notice

Requirements

5+ years building and deploying ML or AI systems, with significant experience in production environments
Strong System Design Skills: ability to design end-to-end AI systems and make sound architectural decisions
Deep AI Expertise: strong experience with LLM systems (agents, tool use, evals) and/or traditional ML where appropriate
Pragmatism: ability to choose the right approach for the problem, balancing complexity, performance, and cost
Evaluation Mindset: experience designing and using evals to drive system improvements
Engineering Excellence: high standards for code quality, testing, and maintainability
Leadership & Mentorship: experience guiding other engineers and influencing technical direction
AI-Native Workflow: strong ability to leverage AI-assisted development tools effectively and thoughtfully

Job Responsibility

System Design & Ownership: design and lead end-to-end AI systems, from problem framing through to production deployment and iteration
Advanced AI Systems & Agents: architect complex agent-based workflows, tool ecosystems, and multi-step reasoning systems
Model Strategy: make decisions on model selection, fine-tuning, and when to use ML vs LLM vs hybrid approaches
Evaluation & Quality: define evaluation frameworks, metrics, and feedback loops to ensure reliability and continuous improvement
Production Excellence: ensure systems are scalable, observable, and robust in real-world environments
Technical Leadership: mentor other engineers, review designs, and raise the bar for engineering and AI practices across the team
AI-Assisted Engineering: drive effective use of AI tooling within the team, improving productivity without compromising quality
Cross-Functional Impact: work closely with product and leadership to shape what we build and why

What we offer

27 days of annual leave (including 3 days Christmas closing) which increases up to 3 days based on tenure, with the option to roll over, buy or sell up to 3 days
Hybrid working with two days a week from our dog-friendly Hoxton office
On-site gym and cycle to work scheme
Employee discount at over 100 retailers
Comprehensive private medical & dental cover with Vitality
Enhanced parental leave pay
Learning & development culture – £1,000 personal annual budget
We’re carbon-neutral and are working towards ambitious carbon reduction goals
Lots of team socials & activities
Annual team retreat

Fulltime

Principal Software Engineer, AI Developer Tools

At Docker, we make app development easier so developers can focus on what matter...

Location

United States , Seattle

Salary:

232000.00 - 319000.00 USD / Year

Docker

Expiration Date

Until further notice

Requirements

10+ years software engineering experience with 3+ years in Staff or Principal Engineer roles
Deep expertise in AI/ML technologies with hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools
Strong understanding of LLM APIs (OpenAI, Anthropic, etc.), prompt engineering, agent orchestration frameworks, and practical applications of AI in software development workflows
Proven track record of architecting and building highly scalable distributed systems and developer-facing platforms
Production experience with modern cloud-native infrastructure including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines
Proficiency in Go (preferred), Rust, Java, or Python with strong software engineering fundamentals
Experience designing developer tools, platform engineering systems, or internal tools that enable other teams
Exceptional product and platform mindset considering business outcomes, developer experience, and technical trade-offs
Strong communication skills with ability to influence technical and non-technical stakeholders across the organization
Track record of technical mentorship and elevating engineering teams' capabilities

Job Responsibility

Define the long-term technical vision and architecture for AI-powered developer tools and the self-service platform that enables teams to build their own AI agents
Establish architectural patterns, technical standards, and best practices for LLM integration, AI agent development, and production AI systems serving developers
Lead technical strategy for platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools
Design highly available, scalable infrastructure for hosting AI agents and developer tools with predictable performance and intelligent resource management
Drive technical decisions on AI technology choices, LLM provider strategies, prompt engineering approaches, and agent orchestration frameworks
Partner with Senior Manager and product leadership to align technical architecture with business objectives and productization opportunities
Architect and build production-ready AI agents for developer productivity including code review assistants, test generators, deployment diagnostics, and incident response automation
Design and implement the self-service platform infrastructure that reduces time-to-production for new AI tools from weeks to days
Build systems that accelerate adoption of AI-native development tools (Claude Code, Cursor, Warp) across Docker's engineering organization
Establish reliability, security, and performance standards for AI systems including SLOs, monitoring, incident response, and cost management

What we offer

Freedom & flexibility
fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup
we want you comfortable while you work
16 weeks of paid Parental leave
Technology stipend equivalent to $100 net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity

Fulltime

Software Engineer II, AI Developer Tools

At Docker, we make app development easier so developers can focus on what matter...

Location

United States , Seattle

Salary:

128000.00 - 181500.00 USD / Year

Docker

Expiration Date

Until further notice

Requirements

2+ years building backend systems, APIs, or developer-facing tools with strong software engineering fundamentals
Proficiency in Go (preferred), Rust, Java, or Python with understanding of data structures, algorithms, and design patterns
Basic understanding of AI/ML concepts with eagerness to learn about LLM APIs, prompt engineering, and AI agent development through hands-on work
Experience with cloud platforms (AWS, GCP, or Azure) and understanding of distributed systems or microservices
Familiarity with CI/CD pipelines, automated testing, version control (Git), and modern development workflows
Strong problem-solving skills with ability to work through technical challenges with guidance from senior engineers
Good communication skills in remote, asynchronous environments with ability to document technical decisions
Collaborative mindset with eagerness to learn from code reviews and feedback
Self-motivated with ability to work autonomously while knowing when to ask for help
Passion for developer tools and user experience

Job Responsibility

Build AI Developer Tool Features: Implement features for AI-powered developer tools such as code review assistants, test generators, deployment diagnostics, and on-call assistance tools
Implement LLM Integrations: Build integrations with LLM APIs (OpenAI, Anthropic, etc.) such as prompt engineering, response handling, error management, and performance optimization
Contribute to Platform Infrastructure: Help build self-service platform capabilities such as deployment pipelines, observability integration, security controls, and operational tooling that enable teams to rapidly deploy AI developer tools
Support AI-Native Development Adoption: Contribute to tools and programs that help teams adopt AI developer tools such as Claude Code, Cursor, and Warp across Docker's engineering organization
Write Quality Code: Develop well-tested code with unit and integration tests
follow team coding standards and participate actively in code reviews to learn best practices
Maintain Production Systems: Assist with monitoring, alerting, and troubleshooting production AI systems
participate in incident response and learn operational best practices
Collaborate and Learn: Work closely with Senior Engineers and Principal Engineer on technical designs
ask questions, seek feedback, and continuously improve your skills in AI/LLM technologies and platform engineering

What we offer

Freedom & flexibility
fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup
we want you comfortable while you work
16 weeks of paid Parental leave
Technology stipend equivalent to $100 net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity

Fulltime

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Senior AI-Native Developer

Job Description

Job Responsibility

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