[Hiring] Software Engineering Senior Advisor @The Cigna Group

Role Description

The Software Engineering Senior Advisor is a hands-on technical leader who designs and steers AI, machine learning operations (MLOps), and data engineering solutions at scale, while partnering closely with business, product, and technology stakeholders to align delivery with strategy, risk, and value.

This is a full-time position for someone who can both build and lead: you contribute to architecture and implementation, and you influence roadmaps, explain tradeoffs, and drive outcomes across teams that may not share the same technical vocabulary.

What you will do

• AI & machine learning engineering:
  • Design and review end-to-end AI/ML solutions: model lifecycle, feature patterns, serving patterns, and integration with business applications.
  • Partner with data science and product teams to turn prototypes into production systems with clear ownership, monitoring, and maintenance paths.
  • Stay current on responsible AI considerations relevant to healthcare and regulated data (e.g., explainability, bias awareness, data governance handoffs).
• MLOps:
  • Define and implement MLOps practices: CI/CD for models, registries, deployment strategies, A/B or shadow deployments where appropriate, and rollback.
  • Ensure observability for models and pipelines: performance drift, data quality, latency, and business-aligned KPIs.
  • Work with security and platform teams on infrastructure, access patterns, and compliance in ML workflows.
• Data Engineering:
  • Lead design of reliable, scalable data pipelines and platforms that feed training, batch scoring, and real-time inference.
  • Promote data quality, lineage, and contract thinking so ML and analytics consumers trust what they build on.
  • Balance build vs. buy (cloud services, feature stores, orchestration) with total cost, maintainability, and team skills.
• Stakeholder Management (core expectation):
  • Translate between business goals and technical options: scope, phasing, risk, and “good enough for now” vs. “must be right first.”
  • Facilitate planning with product owners, legal/compliance, architecture, and operations; document decisions and follow through.
  • Mentor engineers and data practitioners; represent the engineering viewpoint in cross-functional forums without losing sight of delivery.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
• Typically 8+ years of software/data engineering experience, including substantial work in at least two of: ML/AI systems, MLOps, or data engineering at scale.
• Demonstrated experience leading without direct authority: influencing architecture, roadmaps, and multiple teams.

Requirements

• Strong proficiency in Python and/or other languages common in data/ML stacks (e.g., Scala, Java) as used in the target environment.
• Cloud platforms (e.g., AWS, Azure, GCP) and experience with containerization, orchestration (e.g., Kubernetes, Airflow, similar), and CI/CD.
• Data: SQL, batch/streaming patterns, and familiarity with data lakes/warehouses and ELT/ETL.
• ML lifecycle: model packaging, serving (batch and/or online), experiment tracking, and production monitoring.
• Excellent written and verbal communication; ability to run workshops, design reviews, and executive-ready summaries of options and tradeoffs.
• Track record of stakeholder alignment on complex, cross-team initiatives in regulated or enterprise environments (healthcare/insurance a plus).

Benefits

• Comprehensive range of benefits focused on supporting your whole health.
• Health-related benefits including medical, vision, dental, and well-being and behavioral health programs starting on day one.
• 401(k) and company paid life insurance.
• Tuition reimbursement.
• A minimum of 18 days of paid time off per year and paid holidays.