AI Engineering Lead

Blend; Santiago; Presencial; CLP 109.890.000 - 164.835.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

AWS Certifications

Databricks Certification

Snowflake Certification

AI learning paths

Udemy Business access

English lessons

Descripción de la vacante

Blend is seeking an AI Engineering Lead to drive end-to-end AI solutions, aligning data science with production-ready systems. You will mentor engineers, shape proposals, and define risk-aware AI architectures across RAG, prompting, and ML workflows.

The role emphasizes scalable inference, CI/CD for AI models, and collaboration with global teams. Advanced English and 6+ years of hands-on AI delivery are required. LATAM-friendly policies and remote options may apply.

Formación

• 6+ years of experience building and deploying AI solutions in production.
• Advanced English for global collaboration.
• Expert Python, strong Git and ML/LLM versioning practices.

Responsabilidades

• Lead end-to-end project delivery with governance and stakeholder communication.
• Mentor junior engineers and contribute to proposals and new business initiatives.
• Define AI system scope and communicate risks and tradeoffs clearly to clients.
• Design and build RAG systems, agentic frameworks, and LLM-powered solutions for production.
• Apply prompt engineering techniques including instruction design and few-shot sets.
• Lead feasibility assessments among prompting, RAG, fine-tuning, or classical ML.
• Design evaluation frameworks and go/no-go gates with custom metrics.
• Run structured experiments across prompts, retrievers, chunking strategies, and models.
• Identify model failure modes and remediation strategies.
• Build scalable inference infrastructure and CI/CD pipelines for AI/ML models.
• Automate the full MLOps/LLMOps lifecycle and design APIs/microservices.
• Optimize latency, cost, and reliability in orchestration layers.

Conocimientos

Python

Git

ML/LLM versioning

RAG experience

MLOps/LLMOps

APIs and microservices

Communication skills

IaC / infrastructure as code

Herramientas

MLflow

Weights & Biases

Databricks MLOps

AWS

Azure

GCP

Descripción del empleo

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world‑class people and data‑driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

We are seeking an AI Engineering Lead to contribute to our next level of growth and expansion.

Job Description

What is this position about?

• Lead end-to-end project delivery with clear governance and strong stakeholder communication
• Mentor junior engineers and contribute to proposals and new business initiatives
• Define what AI systems should and should not attempt, and communicate risks and tradeoffs transparently to clients
• Design and build RAG systems, agentic frameworks, and LLM-powered solutions robust enough for production
• Apply advanced prompt engineering techniques, including instruction design, few-shot sets, structured outputs, and tool/agent prompts
• Lead feasibility assessments to select the right approach among prompting, RAG, fine-tuning, or classical ML
• Design evaluation frameworks, including LLM-as-a-judge methods, custom metrics (recall@k, precision@k), and go/no-go gates
• Run structured experiments across prompts, retrievers, chunking strategies, and models, grounded in evidence rather than intuition
• Identify and categorize model failure modes, including hallucinations, retrieval misses, and instruction-following errors
• Build scalable inference infrastructure and CI/CD pipelines for AI/ML models
• Automate the full MLOps/LLMOps lifecycle, including tracking, versioning, deployment, monitoring, and retraining
• Design APIs, microservices, and orchestration layers optimized for latency, cost, and reliability

Qualifications

• Expert‑level Python, strong Git practices, and experience with ML/LLM versioning
• Solid cloud experience across AWS, Azure, or GCP (Azure preferred), plus containerization and orchestration
• Hands‑on RAG experience covering chunking, embeddings, retrieval, reranking, and evaluation
• Proven MLOps/LLMOps track record using tools such as MLflow, Weights & Biases, or similar
• Practical evaluation design skills, including metrics, dataset curation, and structured experimentation
• Experience with event‑driven architectures, APIs, and microservices
• Strong communication skills, equally comfortable engaging engineering teams and senior stakeholders
• Preferred: experience with the Databricks MLOps platform, LLM fine‑tuning, building agentic GenAI systems, Infrastructure as Code, security and observability for AI services, a classical ML background, and open‑source contributions

What about languages?

English: Advanced (required for effective communication with global teams)

How much experience must I have?

6+ years of experience building and deploying AI solutions in production environments, with a strong track record across RAG, agentic systems, and MLOps/LLMOps.

Additional Information

Our perks and benefits:

Learning Opportunities:

• Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
• Access to AI learning paths to stay up to date with the latest technologies.
• Study plans, courses, and additional certifications tailored to your role.
• Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
• English lessons to support your professional communication.

Travel opportunities to attend industry conferences and meet clients.

Mentoring and Development:

• Career development plans and mentorship programs to help shape your path.

Celebrations & Support:

• Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
• Company‑provided equipment.

Flexible working options to help you strike the right balance.

Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.