Senior AI Engineer (expression of interest)

Bilue

19d•Hybrid

About The Position

This is an expression of interest for a Senior AI Engineer role at Bilue, a digital consultancy. The role is part of 'The Foundry' and involves working at the intersection of client delivery and internal capability building. It is a hands-on engineering position focused on designing, building, and deploying production-grade AI systems for clients in various sectors, as well as contributing to the development of reference architectures, tooling, and engineering standards for the AI Labs. This is not a research or prompt-engineering role, but rather focuses on building agentic systems, integrating AI into enterprise environments, and establishing production-grade quality standards.

Requirements

Demonstrable experience delivering AI or GenAI solutions in a production environment — not just prototypes or demos.
Strong problem-solving ability and the analytical mindset to work with ambiguous, evolving requirements.
The ability to communicate technical concepts clearly to non-technical stakeholders and client executives.
Genuine systems thought leadership — you understand why the system matters, not just how it works.
A collaborative, low-ego approach, working across teams, clients, and contexts with adaptability.
Comfort operating in a fast moving environment where you’ll work across multiple clients and industries.
Strong opinions, weakly held - curious mind with the ability to rapidly evolve when faced with contradictory evidence.
Strong programming skills in Python; familiarity with TypeScript or Java is a plus.
Hands-on experience with AI and agentic frameworks — LangChain, AgentCore , LlamaIndex, LangGraph, CrewAI, vector databases, or similar.
Working expertise with cloud platforms (AWS, Azure, or GCP)
Solid understanding of data engineering fundamentals — SQL, ETL/ELT, distributed systems, handling large and unstructured datasets.
Experience designing and deploying production AI systems with proper observability, monitoring, and evaluation.
Familiarity with LLMOps practices — prompt versioning, model drift detection, cost monitoring, A/B evaluation.
Understanding of RESTful APIs, microservices, and enterprise integration patterns.

Nice To Haves

Experience with the AWS AI/ML stack (Bedrock, AgentCore, Strands, SageMaker, Lambda, Step Functions).
Familiarity with responsible AI frameworks, bias testing tools, or AI governance practices.
Prior consulting or hyper-scaler experience where you’ve delivered for external clients under real constraints.
Contributions to open-source AI projects, AI research, or published technical writing.

Responsibilities

Design and build production-grade AI solutions including agentic systems, memory systems, LLM-powered features, and intelligent automation for enterprise clients.
Architect cloud-native AI systems on AWS, Azure, or GCP with robust DevOps/LLMOps pipelines for scalability and reliability.
Integrate AI capabilities into existing enterprise platforms (CRM, ERP, lending systems, claims platforms) through well-designed APIs and data pipelines.
Lead AI technical delivery within cross-functional squads alongside designers, strategists, and client stakeholders.
Implement responsible AI practices including red-teaming, bias testing, evaluation harnesses, and human-in-the-loop design.
Contribute to Bilue’s reference architectures for common delivery patterns: knowledge/context pipelines, agentic systems, LLM integrations, and evaluation frameworks.
Help define and evolve engineering standards for AI Labs work — code quality, testing approaches, prompt evaluation frameworks, and what “production-grade” means in practice.
Build reusable tooling, accelerators, and “skills” that make the next project faster and more reliable.
Participate in model evaluation, cost optimisation, and architecture reviews.
Share knowledge across the engineering team through documentation, tech talks, and hands-on mentoring.