AI Lead

Coforge; Oaks (PA); On-site; USD 120,000 - 160,000; Full time

Job summary

Coforge is seeking an AI Leader responsible for defining and executing the artificial intelligence and machine learning strategy. The role involves providing technical leadership to drive innovation and operational efficiency. You will build and mentor high-performing teams and ensure compliance with data privacy and ethical guidelines. The ideal candidate has over 10 years of experience in data science and strong hands-on capabilities with AI frameworks, especially in a financial services context. This position is based in Oaks, Pennsylvania.

Qualifications

• 10+ years experience in data science, machine learning, or advanced analytics.
• 5+ years in a leadership role overseeing AI/ML teams.
• Strong hands-on experience with ML models and statistical methods.

Responsibilities

• Define and own the enterprise AI/ML vision and strategy.
• Lead design and development of AI and machine learning solutions.
• Build and mentor high-performing AI and data science teams.

Skills

Financial services experience

Machine learning models

Python

SQL

Communication skills

AI frameworks

Data governance

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering

Tools

Azure

Docker/Kubernetes

LangChain

Terraform

Job description

The AI Leader is responsible for defining, executing, and scaling the organization’s artificial intelligence and machine learning strategy. This role provides technical and strategic leadership to drive innovation, operational efficiency, and data-driven decision-making across the enterprise. The AI Leader partners closely with Product, Engineering, Data, Risk, Compliance, and Business stakeholders to ensure responsible, scalable, and business-aligned AI solutions.

Key Responsibilities

• Define and own the enterprise AI/ML vision, roadmap, and long-term strategy aligned with business goals
• Lead design, development, deployment, and lifecycle management of AI and machine learning solutions
• Build and mentor high-performing AI, data science, and ML engineering teams
• Partner with Product and Business leaders to identify high-impact AI use cases and prioritize initiatives
• Establish best practices for model development, validation, monitoring, explainability, and retraining
• Ensure AI solutions comply with data privacy, security, regulatory, and ethical AI guidelines
• Oversee AI platform architecture, model pipelines, and MLOps frameworks for scalability and reliability
• Drive adoption of generative AI, predictive analytics, NLP, and advanced modeling techniques where applicable
• Communicate AI strategy, performance, and risks clearly to executive leadership and stakeholders
• Evaluate and manage AI vendors, tools, platforms, and cloud services

Required Qualifications

• Experience with Financial services, Wealth management is preferred to have.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field
• 10+ years of experience in data science, machine learning, or advanced analytics
• 5+ years in a leadership or people-management role overseeing AI/ML teams
• Strong hands‑on experience with ML models, statistical methods, and AI frameworks
• Experience deploying AI solutions in production environments at scale
• Hands on RAG experience: embeddings, retrieval strategies, chunking, metadata/routing, evals, and guardrails.
• Open source frameworks: strong with LangChain (or similar), plus experience with FastAPI/Flask and async patterns.
• Azure: practical experience with Azure OpenAI/Models, Azure AI Search, Azure ML, AKS/Container Apps, Key Vault, App Insights/Log Analytics, and Hybrid Private Networking.
• Terraform: modules, CI/CD integration, and handling nested data structures.
• MLOps/DevOps: Docker/Kubernetes, CI/CD (Gitlab or Azure DevOps), secrets management, and automated testing.
• Solid understanding of LLMs (prompting, function/tool calling, structured outputs, rate limiting, token/cost management).
• Proficiency with Python, SQL, and modern data/ML platforms (cloud-based preferred)
• Strong understanding of data governance, model risk management, and responsible AI practices
• Excellent communication skills with the ability to translate complex AI concepts for non-technical audiences

Preferred / Nice-to-Have

• Experience in financial services, healthcare, life sciences, or other regulated industries
• Exposure to generative AI, large language models (LLMs), and prompt engineering
• Familiarity with MLOps tools, CI/CD for ML, and cloud platforms (AWS, Azure, or GCP)
• Experience driving enterprise AI transformation or center-of-excellence models
• Prior ownership of AI compliance, audit, or regulatory reviews