Senior AI Engineer

About the Role:

Join Abacus Insights to architect and implement cutting-edge AI platforms that power healthcare innovation. As a Senior AI Engineer, you’ll provide technical leadership, mentor teams, and partner with engineering leaders on strategic initiatives to scale AI capabilities across the organization.

What you'll do:

• Architect and Implement AI Platforms - Design and build scalable AI systems and platforms that power Abacus products and services.
• Shape AI Strategy and Features - Define the direction of applied AI and intelligence features, deploying state-of-the-art models and technologies (e.g., Abacus Agents, MCP, SQL and RAG tools).
• Develop Advanced AI Solutions - Create novel data collection methods, fine-tuning strategies, and LLM technologies optimized for specific tasks and domains.
• Build Robust ML Pipelines - Implement end-to-end pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and evaluation to enable rapid experimentation and iteration.
• Scale GenAI Infrastructure - Develop reusable backend systems for GenAI products, including logging, telemetry, and evaluation frameworks for reliable performance.
• Lead Critical AI Projects - Drive initiatives focused on AI innovation, development productivity, and benchmarking to accelerate delivery and quality.
• Collaborate Across Teams - Work closely with AI engineers, data engineers, product teams, and business stakeholders to deliver impactful solutions that enhance user experience.
• Mentor and Coach - Guide development teams, enforce coding standards, and foster best practices in architecture and agile methodologies.
• Influence Architecture Decisions - Participate in software design discussions, ensuring consistency and alignment with organizational strategy.
• Optimize Processes - Identify and implement improvements for Agile/Scrum teams, especially in fast-moving AI projects.
• Ensure Delivery Excellence - Manage timelines, quality standards, and communication around architecture and implementation objectives.
• Maintain Operational Readiness - Balance roadmap commitments with incident management, configuration management, and client escalations.
• Champion Security and Compliance - Protect confidential data and ensure adherence to security and regulatory standards.

What we expect from you:

• 3+ years of ML/AI engineering experience in high-growth environments or equivalent academic research background.
• 3+ years of software development experience at some point in your career.
• 2+ years working with Databricks, Mosaic AI Gateway, and related Data+AI technologies.
• Proven expertise in language modeling and GenAI, including generative and embedding techniques, fine-tuning, evaluation benchmarks, agentic workflows (orchestration, observability, debugging), RAG, SQL Agents, and MCP.
• Proficiency in Python, TensorFlow/PyTorch, and scalable ML/AI architectures.
• Ability to deliver end-to-end model and system development—from research and prototyping to deployment and monitoring.
• Strong coding skills and familiarity with software engineering best practices (testing, code reviews, deployment).
• Experience designing scalable, distributed systems for data processing (10s–100s TB).
• Broad technical depth to influence and lead discussions with internal and external stakeholders.
• Understanding of adjacent roles (product, project management, client delivery, operations) and ability to collaborate effectively.
• Track record of leading engineering teams or projects to deliver production-grade systems.

What we like to see, but not required:

• Snowflake, FHIR, Healthcare Data exposure