Prompt Engineer & AI Applications Lead 
(Madrid, Spain or Bengaluru, India — Hybrid/Flexible) 

About the Role 

Cigna is accelerating responsible AI adoption across the enterprise. We’re seeking a Prompt Engineer & AI Applications Lead to partner with product, data, engineering, and business stakeholders to discover, evaluate, and scale AI use cases—while ensuring safety, compliance, and measurable value. This role blends hands‑on prompt design with business relationship management and vendor collaboration to drive outcomes across multiple time zones. 

What You’ll Do (Key Responsibilities) 

AI Use Case Discovery & Shaping 

• Identify, qualify, and prioritize high‑impact AI opportunities across functions (operations, clinical, customer support, finance, IT). 

• Facilitate discovery workshops to define problem statements, success metrics, guardrails, and adoption plans. 

• Translate business needs into AI solution patterns (e.g., retrieval‑augmented generation, summarization, classification, extraction, assistants/agents). 

Prompt Engineering & Experimentation 

• Design, test, and optimize prompts, chains, and system instructions for performance, safety, and reliability across multiple LLMs and tools. 

• Develop prompt evaluation frameworks (A/B tests, golden sets, bias & hallucination checks, cost/latency tracking). 

• Create reusable prompt templates, style guides, and prompt libraries for enterprise use. 

Vendor & Partner Management 

• Assess AI vendors for capability, compliance, total cost of ownership, integration complexity, and roadmap fit. 

• Co‑develop POCs/pilots with vendors; define SLAs, acceptance criteria, and transition plans to scale or sunset. 

• Coordinate security, privacy, legal, and procurement reviews; document decisions and risks. 

Solution Delivery & Governance 

• Partner with Data/ML Engineering to integrate RAG pipelines, guardrails, and observability (prompt logs, red‑teaming results, monitoring). 

• Ensure adherence to responsible AI, data privacy, and healthcare compliance requirements (e.g., PHI handling, HIPAA‑aligned processes in consultation with compliance teams). 

• Contribute to model cards, risk assessments, and human‑in‑the‑loop controls. 

Stakeholder Enablement & BRM 

• Serve as a trusted advisor to business leaders—clarify value cases, manage expectations, and align roadmaps and budgets. 

• Build enablement materials (playbooks, demos, FAQs) and deliver training for non‑technical and technical audiences. 

• Communicate progress, risks, and ROI via clear narratives and dashboards. 

What You’ll Bring (Qualifications) 

Must‑Have 

• 5+ years of relevant experience in AI/ML product work, data‑driven solutions, or technical consulting, with at least 2+ years hands‑on prompt engineering (or demonstrable expertise). 

• Business Relationship Management (BRM) experience: stakeholder alignment, requirements shaping, roadmap facilitation, and value realization. 

• Proficiency with LLMs and tooling (e.g., prompt design, few‑shot techniques, function calling/tools, vector search/RAG, evaluation methods). 

• Practical knowledge of data fundamentals (data quality, governance, metadata, PII/PHI concepts) and safe AI patterns. 

• Strong communication: can translate complex AI concepts for executives and non‑technical teams; excellent storytelling and documentation. 

• Collaborative mindset and experience working across multiple time zones and cross‑functional teams. 

• Bachelor’s degree in a relevant field (Computer Science, Data/AI, Engineering, or related); equivalent experience considered. 

• Location: Madrid, Spain or India (major hubs such as Bengaluru/Hyderabad/Pune preferred; flexible). 

Nice‑to‑Have 

• Experience in healthcare/insurance processes and analytics. 

• Familiarity with evaluation frameworks (e.g., golden datasets, rubric‑based scoring), guardrails/red‑teaming, and observability. 

• Exposure to MLOps/LangChain/LlamaIndex, vector databases, and API integration patterns. 

• Practical understanding of responsible AI principles and risk controls; experience partnering with Legal/Privacy/Compliance. 

• Comfort with one or more languages or tools (Python, SQL, REST APIs, YAML), and with cloud platforms (Azure/AWS/GCP). 

Success Metrics (KPIs) 

• Validated use cases discovered per quarter and percent advancing from POC → Pilot → Scale. 

• Model quality gains (e.g., accuracy, factuality, reduction in hallucination) and experience metrics (latency, cost per task). 

• Risk reduction (guardrail coverage, incident rate, red‑team findings addressed). 

• Stakeholder satisfaction (NPS/CSAT) and enablement reach (teams trained, assets reused). 

• Vendor outcomes (SLA adherence, value realization, cost savings/avoidance). 

Ways of Working 

• Hybrid work with core collaboration hours overlapping European and India time zones; occasional evening/morning meetings to align with global teams. 

• Limited travel for workshops or vendor evaluations as needed. 

• Partner closely with Product Owners, Data/ML Engineering, Architecture, Security, Privacy, Legal, and Procurement.