Senior AI Enginee
Employment Info
JOB DETAILS
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.
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 (leveraging AI of course).
- Lead AI technical delivery within cross-functional squads alongside designers, strategists, and client stakeholders — translating complex AI concepts into high-impact outcomes.
- Implement responsible AI practices including red-teaming, bias testing, evaluation harnesses, and human-in-the-loop design before anything ships.
- 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 that sharpen Bilue’s technical edge.
- Share knowledge across the engineering team through documentation, tech talks, and hands-on mentoring.
Desired Qualifications
- 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.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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