{ “@context”: “http://schema.org”, “@type”: “JobPosting”, “title”: “AI Native Software Engineer”, “description”: “
Overview:
TekWissen Group is a workforce management provider throughout the UK, Europe and many other countries in the world. The client below is a global professional services company with leading capabilities in digital, cloud, and security. Combining unmatched experience and specialized skills across more than 40 industries
Role: AI Native Software Engineer
Location: London, UK
Work type: Hybrid
Duration: 6 Months
Job Summary:
- We are seeking a hands‑on AI Native Software Engineer to design, build, and deploy production‑grade AI‑driven systems within complex enterprise environments.
- In this role, you will focus on agent‑based architectures, AI platform integration, and cloud‑native development, delivering scalable, reliable solutions that power real business workflows.
- This is a 100% hands‑on engineering role, ideal for a senior technologist who thrives at the intersection of AI systems, software engineering, and cloud infrastructure.
Key Responsibilities:
Core Duties
- Design, implement, and maintain AI agent workflows, including retrieval‑augmented generation (RAG), orchestration, tool/function invocation, and policy‑based routing
- Build cloud‑native backend services and APIs to support AI‑driven applications and enterprise integrations
- Implement evaluation, monitoring, and observability frameworks to ensure accuracy, latency, reliability, and system health across AI agent lifecycles
- Optimize AI and system performance across cost, scalability, and latency dimensions in production environments
Deliverables or Project Scope
- Production‑ready AI‑powered applications aligned to defined business workflows and enterprise standards
- Scalable multi‑model and multi‑provider AI architectures, including abstraction layers for provider flexibility
- Fully deployed cloud‑native services using microservices, containers, and serverless or event‑driven patterns
- Robust CI/CD pipelines, infrastructure‑as‑code implementations, logging, monitoring, and fault‑tolerant deployments
Collaboration Tools or Platforms
- Microsoft Office (Excel, Word, Outlook, Teams)
- AI Platforms & Models: OpenAI, Anthropic (Claude), Google Vertex AI, and select open‑source models
- Agent & Orchestration Frameworks: LangGraph, AutoGen, CrewAI (or similar)
- Cloud & DevOps Tooling: Docker, Kubernetes, Terraform, Helm, CI/CD pipelines
- Enterprise Integration: APIs, enterprise platforms, monitoring and observability tools
Why You’ll Love This Role
- Build real, enterprise‑grade AI systems that move beyond experimentation into production
- Remain deeply technical in a 100% hands‑on engineering role with no people‑management responsibilities
- Work with modern AI platforms, multi‑model architectures, and cloud‑native technologies
- Focus on high‑impact delivery with clear scope, measurable outcomes, and implementation ownership
- Collaborate with experienced engineering teams in an execution‑driven environment
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field or equivalent practical experience
- 8–10+ years of professional software engineering experience with ownership of production systems
- 3+ years of hands‑on experience building and deploying AI/LLM‑based systems in production (agents, RAG pipelines, orchestration)
- Strong experience designing and delivering cloud‑native systems, including APIs, microservices, containers, and serverless or event‑driven architectures
- Proficiency in Python, Java, or comparable backend languages
- Hands‑on experience with CI/CD pipelines, infrastructure as code, and monitoring or observability tools
- Proven ability to deliver production‑quality code, including testing, debugging, performance tuning, and operational readiness
Preferred Qualifications
- Experience with agent frameworks such as LangGraph, AutoGen, CrewAI, or similar
- Experience designing multi‑agent or distributed AI systems
- Familiarity with multi‑model and multi‑provider AI architectures
- Experience integrating AI solutions into enterprise‑scale systems or platforms
- Demonstrated experience optimizing AI workloads for cost, performance, and latency
Additional Information / Requirements
- This is a 100% hands‑on engineering role with no people‑management responsibilities
- Strong problem‑solving skills and technical judgment in complex enterprise environments
- Ability to collaborate effectively with internal and client engineering teams
- Comfortable working within existing architecture standards, security requirements, and engineering best practices
- Strong written and verbal communication skills for technical documentation and design discussions
TekWissen® Group is an equal opportunity employer supporting workforce diversity
”, “datePosted”: “2026-05-15”, “hiringOrganization”: { “@type”: “Organization”, “name”: “TekWissen UK”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__433381770__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=33” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “London” } } }Company: TekWissen UK
Location: London
Job Description:
Overview:
TekWissen Group is a workforce management provider throughout the UK, Europe and many other countries in the world. The client below is a global professional services company with leading capabilities in digital, cloud, and security. Combining unmatched experience and specialized skills across more than 40 industries
Role: AI Native Software Engineer
Location: London, UK
Work type: Hybrid
Duration: 6 Months
Job Summary:
- We are seeking a hands‑on AI Native Software Engineer to design, build, and deploy production‑grade AI‑driven systems within complex enterprise environments.
- In this role, you will focus on agent‑based architectures, AI platform integration, and cloud‑native development, delivering scalable, reliable solutions that power real business workflows.
- This is a 100% hands‑on engineering role, ideal for a senior technologist who thrives at the intersection of AI systems, software engineering, and cloud infrastructure.
Key Responsibilities:
Core Duties
- Design, implement, and maintain AI agent workflows, including retrieval‑augmented generation (RAG), orchestration, tool/function invocation, and policy‑based routing
- Build cloud‑native backend services and APIs to support AI‑driven applications and enterprise integrations
- Implement evaluation, monitoring, and observability frameworks to ensure accuracy, latency, reliability, and system health across AI agent lifecycles
- Optimize AI and system performance across cost, scalability, and latency dimensions in production environments
Deliverables or Project Scope
- Production‑ready AI‑powered applications aligned to defined business workflows and enterprise standards
- Scalable multi‑model and multi‑provider AI architectures, including abstraction layers for provider flexibility
- Fully deployed cloud‑native services using microservices, containers, and serverless or event‑driven patterns
- Robust CI/CD pipelines, infrastructure‑as‑code implementations, logging, monitoring, and fault‑tolerant deployments
Collaboration Tools or Platforms
- Microsoft Office (Excel, Word, Outlook, Teams)
- AI Platforms & Models: OpenAI, Anthropic (Claude), Google Vertex AI, and select open‑source models
- Agent & Orchestration Frameworks: LangGraph, AutoGen, CrewAI (or similar)
- Cloud & DevOps Tooling: Docker, Kubernetes, Terraform, Helm, CI/CD pipelines
- Enterprise Integration: APIs, enterprise platforms, monitoring and observability tools
Why You’ll Love This Role
- Build real, enterprise‑grade AI systems that move beyond experimentation into production
- Remain deeply technical in a 100% hands‑on engineering role with no people‑management responsibilities
- Work with modern AI platforms, multi‑model architectures, and cloud‑native technologies
- Focus on high‑impact delivery with clear scope, measurable outcomes, and implementation ownership
- Collaborate with experienced engineering teams in an execution‑driven environment
Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field or equivalent practical experience
- 8–10+ years of professional software engineering experience with ownership of production systems
- 3+ years of hands‑on experience building and deploying AI/LLM‑based systems in production (agents, RAG pipelines, orchestration)
- Strong experience designing and delivering cloud‑native systems, including APIs, microservices, containers, and serverless or event‑driven architectures
- Proficiency in Python, Java, or comparable backend languages
- Hands‑on experience with CI/CD pipelines, infrastructure as code, and monitoring or observability tools
- Proven ability to deliver production‑quality code, including testing, debugging, performance tuning, and operational readiness
Preferred Qualifications
- Experience with agent frameworks such as LangGraph, AutoGen, CrewAI, or similar
- Experience designing multi‑agent or distributed AI systems
- Familiarity with multi‑model and multi‑provider AI architectures
- Experience integrating AI solutions into enterprise‑scale systems or platforms
- Demonstrated experience optimizing AI workloads for cost, performance, and latency
Additional Information / Requirements
- This is a 100% hands‑on engineering role with no people‑management responsibilities
- Strong problem‑solving skills and technical judgment in complex enterprise environments
- Ability to collaborate effectively with internal and client engineering teams
- Comfortable working within existing architecture standards, security requirements, and engineering best practices
- Strong written and verbal communication skills for technical documentation and design discussions
TekWissen® Group is an equal opportunity employer supporting workforce diversity
…
Posted: May 15th, 2026