Associate AI Engineer, OI&A

Career Category

Sales & Marketing Operations

Job Description

Associate AI Engineer, OI&A

Associate Data Scientist, Obesity Intelligence & Analytics

What you will do

Let’s do this. Let’s change the world. In this vital role, you’ll join a fun, innovative technology operations and data enablement team within the Obesity Intelligence & Analytics (OI&A) organization. You will deliver advanced data science, software engineering, and GenAI solutions that enable commercial and non-commercial functions across the enterprise.

You will maintain technical continuity across the lifecycle, working with business stakeholders and multidisciplinary teams to shape the simplest viable solution, coordinate execution, make delivery trade-offs, remove blockers and contribute hands-on to critical components. The role combines enterprise solution engineering, applied AI/ML, GenAI, RAG and agents, integration, evaluation, MLOps/LLMOps, security, governance and production operations. Technical accountability complements, but does not replace, explicit product, business, compliance and long-term support ownership.

Responsibilities

• Lead discovery by clarifying the business workflow, users, intended outcome, value hypothesis, acceptance criteria, operational constraints, data readiness, integration dependencies and production implications;
• Translate complex problems into an executable solution design, delivery plan, technical workstreams, estimates, milestones, dependencies, risks, acceptance criteria, release approach and support transition.
• Build, prototype, review or contribute to critical production components to prove feasibility or unblock delivery, including AI-enabled applications, RAG, bounded agents, intelligent automation, APIs and integrations.
• Define and maintain the integrated architecture across applications, workflows, data and knowledge pipelines, models, retrieval, agents, APIs, enterprise integrations, identity, access controls, observability and human review.
• Orchestrate delivery across full-stack software and AI engineering, data science, ML and context engineering, testing, platform, security, compliance and business roles;
• Establish integrated testing, AI evaluation and governance covering functional, performance, security, data, model, retrieval, generation, tool-use, human-oversight and operational behavior with explicit release thresholds.
• Coordinate production readiness through CI/CD, staged release, monitoring, logging, SLOs, rollback, recovery, runbooks and controlled deployment; support early issue triage, stabilization and transition to the operating owner.
• Communicate evidence, risks, trade-offs and status clearly; measure adoption and value and convert delivery lessons into reusable components, accelerators, standards, documentation and playbooks.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The dynamic professional we seek is a collaborative professional with the following qualifications.

Basic Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Data Science or related field OR
• Diploma with 2+ years of experience in Computer Science, Engineering, Data Science, or related field

Preferred Qualifications:

• Enterprise solution architecture and integration: End-to-end design across applications, APIs, services, data and knowledge flows, models, retrieval, agents, workflows, persistence, identity, security zones, enterprise systems and support boundaries.
• Applied AI/ML and GenAI engineering: Production Python and SQL; classical ML and NLP awareness; foundation-model integration, prompt and context management, RAG, structured output, provenance, citations, bounded tool use, permissions, recovery and human control.
• Cloud, DevSecOps and lifecycle operations: Cloud-native services, containers, CI/CD, infrastructure as code, versioning, observability, SLOs, staged release, rollback, incidents, disaster recovery, capacity, FinOps, runbooks and MLOps/LLMOps.
• Strong hands-on proficiency in Python and SQL, with experience designing or reviewing production software, APIs, services, data flows, evaluation pipelines and enterprise integrations.
• Proven ability to turn complex business problems into coherent technical designs, executable delivery plans, acceptance criteria and production-readiness evidence while coordinating multidisciplinary teams.
• Advanced capability in at least one role-defining pillar—Applied AI/ML, GenAI/RAG/agents, full-stack and integration engineering, or AI platform/MLOps—plus credible breadth across the production lifecycle.
• Advanced RAG, knowledge and agent systems: Hybrid or graph retrieval, knowledge graphs, source verification, MCP-style integration, durable or multi-agent workflows, policy enforcement and adversarial testing.
• Experienced with Databricks, AWS, Spark, LLMs, and agentic development solutions is a plus. Additionally, experience in life sciences, healthcare, payor, or pharmaceutical environments will be factored in.

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