AI ENGINEERING MANAGER

Blend360

Full-timesenior

Job description

Leadership and Delivery<ul><li>Lead project delivery end to end, with clear governance, stakeholder communication, and accountability for outcomes</li><li>Build and mentor a high-performing AI engineering team, establishing technical standards and fostering a culture of quality and pragmatism</li><li>Own proposals and new business initiatives, defining technical feasibility and communicating risks and tradeoffs clearly to clients</li><li>Define what AI systems should and should not attempt, setting realistic expectations and being upfront about limitations</li><li>Conduct technical reviews and architectural assessments to maintain high standards across projects and team</li></ul>AI Development<ul><li>Guide the design and delivery of RAG systems, agentic frameworks, and LLM-powered solutions that are robust enough for production</li><li>Lead the application of advanced prompt engineering techniques including instruction design, few-shot sets, structured outputs, and tool/agent prompts</li><li>Run feasibility assessments to choose the right approach for each problem: prompting, RAG, fine-tuning, or classical ML</li><li>Mentor engineers on end-to-end AI system design and production deployment practices</li></ul>Evaluation and Quality<ul><li>Design evaluation frameworks including LLM-as-a-judge approaches, metric creation (recall@k, precision@k), and go/no-go gates</li><li>Lead structured experiments across prompts, retrievers, chunking strategies, and models, grounded in evidence not intuition</li><li>Establish team practices for identifying and categorising model failures including hallucinations, retrieval misses, and instruction-following errors</li><li>Set quality standards that ensure AI systems meet production reliability requirements</li></ul>MLOps and Infrastructure<ul><li>Build scalable inference infrastructure and CI/CD pipelines for AI/ML models that support rapid iteration and reliable deployment</li><li>Automate the full MLOps/LLMOps lifecycle: tracking, versioning, deployment, monitoring, and retraining across the team</li><li>Design APIs, microservices, and orchestration layers optimised for latency, cost, and reliability</li><li>Lead infrastructure decisions that balance technical excellence with business efficiency</li></ul> What We Are Looking For<ul><li>7+ years building and deploying AI solutions in production environments</li><li>2+ years of direct team leadership or technical management experience</li><li>Expert Python proficiency, strong Git practices, and experience with ML/LLM versioning and deployment</li><li>Solid cloud experience across AWS, Azure, or GCP—preference for Azure—plus containerisation and orchestration knowledge</li><li>Hands-on RAG experience covering chunking, embeddings, retrieval, reranking, and evaluation</li><li>Proven MLOps/LLMOps track record using tools like MLflow, Weights and Biases, or similar</li><li>Practical evaluation design skills: metrics, dataset curation, and structured experimentation</li><li>Experience with event-driven architectures, APIs, and microservices</li><li>A clear communicator equally comfortable with engineering teams and senior stakeholders</li><li>Strong hiring and team-building instincts with proven mentoring experience</li></ul>What about languages?<ul><li>English: Advanced (required for effective communication with global teams and client leadership).</li></ul>How much experience must I have?7+ years of hands-on AI/ML engineering experience in production environments, with 2+ years of direct team leadership or technical management responsibility.Nice to Have<ul><li>Databricks MLOps platform</li><li>LLM fine-tuning experience</li><li>Building agentic GenAI systems</li><li>Infrastructure as Code</li><li>Security and observability for AI services</li><li>Classical ML background</li><li>Open-source contributions</li></ul> Our Perks and Benefits:📚 Learning Opportunities:<ul><li>Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.</li><li>Access to AI learning paths to stay up to date with the latest technologies.</li><li>Study plans, courses, and additional certifications tailored to your role.</li><li>Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.</li><li>English lessons to support your professional communication.</li></ul>👨🏽‍💻 Travel opportunities to attend industry conferences and meet clients.👩‍🏫 Mentoring and Development:<ul><li>Career development plans and mentorship programs to help shape your path.</li></ul>🎁 Celebrations & Support:<ul><li>Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.</li><li>Company-provided equipment.</li></ul>⚖️ Flexible working options to help you strike the right balance.🏥 Statutory Benefits:<ul><li>Social security coverage (IMSS).</li><li>Christmas bonus (Aguinaldo) as per Mexican law.</li><li>Vacation premium (Prima Vacacional).</li><li>Remote work bonus.</li><li>Paid leaves as per Federal Labor Law (LFT).</li><li>Additional benefits as required by Mexican labor regulations.</li></ul>Other benefits may vary. For detailed information, please consult with one of our recruiters.