AI Engineer (6 months contract)
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Key skills for this role
About the Role
Contango seeks an experienced AI Engineer for a 6-month contract in Abu Dhabi. You will design, build, and deploy production-grade AI systems including LLM applications, RAG pipelines, and agentic workflows.
Key Skills for This Role
Responsibilities
- Design and deliver end to end LLM applications from prototype to production
- Build and optimize RAG pipelines including data parsing, ingestion, chunking, embeddings, vector search, re ranking, and context window optimization
- Design and orchestrate agentic workflows for reasoning, planning, and task execution
- Build evaluation and observability: define metrics, run eval pipelines, and monitor systems in production
- Integrate AI components into client applications via secure backend APIs
- Engineer the supporting data layer: pipelines, feature/embedding stores, and data quality for AI workloads on cloud platforms
- Manage the full lifecycle: deployment, monitoring, versioning, rollback readiness, and cost/performance optimization
- Translate business problems into AI solutions and communicate trade offs to clients and stakeholders
- Maintain technical documentation, runbooks, and delivery artifacts
Requirements
- Demonstrated experience delivering AI solutions in an enterprise or client facing/consulting environment
- Strong Python and solid software engineering fundamentals
- Hands on LLM APIs (Anthropic, OpenAI, Azure OpenAI)
- Proven RAG architecture experience with vector databases
- Experience with agent/orchestration frameworks (LangChain, LangGraph, CrewAI)
- Evaluation and observability skills for production AI
- Working knowledge of a major cloud AI/data stack (Azure, AWS, or GCP) and MLOps tooling
- Solid data engineering skills: SQL, distributed processing (e.g., Spark/Databricks)
- Strong collaboration and communication skills
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field
- 3–6 years of experience building and shipping AI/ML solutions into production
Full Job Posting
Role Overview
- Contract duration: 6 months (with potential extension).
- Engagement Type: Full time.
- Start date: July 2026.
- Location: Abu Dhabi (on site).
- We are seeking an experienced AI Engineer to design, build, and deploy production grade AI systems — primarily LLM powered applications, RAG pipelines, and agentic workflows.
Key Responsibilities
- Design and deliver end to end LLM applications: scope the use case, build, evaluate, deploy, and hand over reliable, observable services.
- Build and optimize RAG pipelines: data parsing, ingestion, chunking, embeddings, vector search, re ranking, and context window optimization.
- Design and orchestrate agentic workflows for reasoning, planning, and task execution.
- Build evaluation and observability: define metrics (accuracy, latency, cost per task), run eval pipelines, and monitor systems in production.
- Integrate AI components into client applications via secure backend APIs; collaborate with data, software, and DevSecOps teams.
- Engineer the supporting data layer: pipelines, feature/embedding stores, and data quality for AI workloads on cloud platforms.
- Manage the full lifecycle: deployment, monitoring, versioning, rollback readiness, and cost/performance optimization.
- Translate business problems into AI solutions and communicate model capabilities, limitations, and trade offs clearly to clients and stakeholders.
- Maintain technical documentation, runbooks, and delivery artifacts across Design & Align → Build → UAT → Production & Hypercare.
Candidate Requirements
- Demonstrated experience delivering AI solutions in an enterprise or client facing/consulting environment.
- Prior experience at management consulting firms and/or Big Tech is an advantage.
- Strong Python and solid software engineering fundamentals.
- Hands on LLM APIs (Anthropic, OpenAI, Azure OpenAI), including tokenization, latency, and cost control.
- Proven RAG architecture experience with vector databases (e.g., Azure AI Search, Qdrant, Chroma, Pinecone, FAISS).
- Experience with agent/orchestration frameworks (e.g., LangChain, LangGraph, CrewAI).
- Evaluation and observability skills for production AI (eval pipelines, LLM as judge, monitoring).
- Working knowledge of a major cloud AI/data stack (Azure, AWS, or GCP) and MLOps tooling (e.g., MLflow, Docker).
- Solid data engineering skills: SQL, distributed processing (e.g., Spark/Databricks).
- Strong collaboration and communication skills — able to work with both technical teams and senior client stakeholders.
Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- 3–6 years of experience building and shipping AI/ML solutions into production.
- Preferred certifications (nice to have): cloud AI certifications (Azure AI Engineer, AWS ML, Databricks GenAI Engineer).
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