AI Engineer
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Key skills for this role
About the Role
Infinite pl is seeking an AI Engineer to design and build agentic AI solutions from concept to production. The role involves developing agent loops, RAG flows, and evaluation bundles, with a focus on practical LLM and agentic AI delivery.
Key Skills for This Role
Responsibilities
- Design and build agentic AI solutions from concept to pilot or production, including agent role definition, autonomy boundaries, tool/data scopes, guardrails, and evaluation criteria
- Implement agent loops, tool use patterns, context engineering, retrieval/RAG flows, HITL approval journeys, tracing, telemetry, and audit capture
- Select and justify models based on latency, cost, residency, reliability, and use case fit; tune solutions for performance and operational cost
- Develop reusable Agent JD templates, prompt/context patterns, orchestration patterns, and evaluation assets for cross team adoption
- Partner with governance, platform, and integration teams to make agents gate ready by design, including prompt injection, PII leakage, and reliability controls
- Support complex and multi agent solutions, including orchestration, memory, retrieval, reasoning, and agent to agent composition
- Move solutions through sandbox, staging, and production promotion paths, ensuring each agent is observable, versioned, tested, and auditable
- Mentor junior engineers and contribute to a strong engineering culture around quality, speed, learning, and responsible AI delivery
Requirements
- Strong software engineering background in Python and/or C# with production grade APIs, services, or cloud native applications
- Hands on experience with LLMs, agent frameworks, and agentic design patterns (Semantic Kernel, Microsoft Agent Framework / AutoGen, LangGraph, or comparable)
- Practical experience with RAG, vector search, prompt/context engineering, system prompt design, tool calling, and model evaluation
- Ability to build and maintain evaluation sets, regression tests, and acceptance criteria for agent behaviour, reliability, and safety
- Experience integrating APIs, data sources, and tools into AI workflows
- Understanding of cloud native delivery, observability, CI/CD, secrets management, telemetry, and secure software development practices
- Strong communication skills to explain technical trade offs to stakeholders
Full Job Posting
About Infinite Pl
- Infinite pl is a digital led tech firm driven to become a digital logistics pioneer by harnessing the power of people, data, and platforms.
Role Summary
- We are looking for an AI Engineer who can turn priority use cases into working, evaluable agents.
Key Responsibilities
- Design and build agentic AI solutions from concept to pilot or production, including agent role definition, autonomy boundaries, tool/data scopes, guardrails, and evaluation criteria
- Implement agent loops, tool use patterns, context engineering, retrieval/RAG flows, HITL approval journeys, tracing, telemetry, and audit capture
- Select and justify models based on latency, cost, residency, reliability, and use case fit; tune solutions for performance and operational cost
- Develop reusable Agent JD templates, prompt/context patterns, orchestration patterns, and evaluation assets that can be adopted across teams
- Partner with governance, platform, and integration teams to make agents gate ready by design, including prompt injection, PII leakage, and reliability controls
- Support complex and multi agent solutions, including orchestration, memory, retrieval, reasoning, and agent to agent composition
- Move solutions through sandbox, staging, and production promotion paths, ensuring each agent is observable, versioned, tested, and auditable
- Mentor junior engineers and contribute to a strong engineering culture around quality, speed, learning, and responsible AI delivery
Key Requirements
- Strong software engineering background in Python and/or C#, with experience building production grade APIs, services, or cloud native applications
- Hands on experience with LLMs, agent frameworks, and agentic design patterns such as Semantic Kernel, Microsoft Agent Framework / AutoGen, LangGraph, or comparable frameworks
- Practical experience with RAG, vector search, prompt/context engineering, system prompt design, tool calling, and model evaluation
- Ability to build and maintain evaluation sets, regression tests, and acceptance criteria for agent behaviour, reliability, and safety
- Experience integrating APIs, data sources, and tools into AI workflows; comfortable debugging across application, data, and model layers
- Understanding of cloud native delivery, observability, CI/CD, secrets management, telemetry, and secure software development practices
- Strong communication skills with the ability to explain technical trade offs to product, business, governance, and leadership stakeholders
Preferred Qualifications
- Azure AI Foundry, Azure OpenAI, Azure AI Search, Functions, Container Apps, Cosmos DB, Redis, OpenTelemetry, or equivalent cloud AI stack experience
- Experience with bilingual or Arabic/English AI products, evaluation design, and user facing AI experiences
- Experience with multi modal AI, including vision, voice, document intelligence, or video/avatar experimentation
- Prior work in government, regulated, sovereign cloud, or enterprise environments where auditability and data residency matter
- Technical leadership or player coach experience, including mentoring engineers and raising engineering standards
TECH STACK / TOOLS
- Azure AI Foundry Semantic Kernel LangGraph Azure OpenAI AI Search Cosmos DB Redis Functions, Container Apps Eval harness OpenTelemetry
FIRST 90 DAYS SUCCESS
- At least one agent progresses through the full factory path into production or production equivalent validation on a real source, with a passing evaluation bundle
- A reusable Agent JD, prompt/context, or orchestration pattern is contributed to the team library
- The AI engineering team improves first time gate readiness through better patterns, testing, and documentation
This role is not.
- A pure model research role or a platform/landing zone owner. This role builds working agents and the patterns that make them reliable.
Hiring Process
- We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assis
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