Lead the architecture, design, and hands‑on development of enterprise Generative AI and Agentic AI solutions.
Compensation
The annual salary for this position is between $100,000 to $150,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Responsibilities
Lead the architecture, design, and hands‑on development of enterprise Generative AI and Agentic AI solutions.
Architect and build scalable AI applications, copilots, intelligent agents, and reusable accelerators using modern large language models and agent orchestration frameworks.
Design solutions leveraging Retrieval‑Augmented Generation (RAG), vector databases, prompt engineering, and context engineering to address complex enterprise use cases.
Leverage AWS Bedrock, GitHub Copilot, Claude Code, and other AI‑assisted engineering tools to accelerate software delivery and enhance developer productivity.
Establish reusable AI engineering patterns and utilities that support cloud‑native architecture, CI/CD practices, and enterprise software engineering standards.
Lead the design and delivery of reusable enterprise assistants, agents, AI services, skills, and agentic workflows for Wellmark’s Enterprise AI Services & Agents team, combining solution design, software engineering, customer engagement, and end‑to‑end accountability for secure, scalable, and supportable AI solutions.
Responsibilities
Lead solution design and delivery of enterprise AI services and agents
Partner with engineers, customers, product leaders, architecture, security, and governance stakeholders to translate business needs into production‑ready solutions
Establish enterprise blueprints and engineering standards for assistants, agents, agentic workflows, and AI evaluation
Build reusable frameworks and components to reduce duplication and accelerate governed AI delivery
Mentor and coach engineering team members
Requirements
Bachelor’s degree in Computer Science, MIS, or related field
Nice to have: AWS certifications such as AWS Certified Developer, Solutions Architect, or Machine Learning Engineer
Senior Principal Software Architect focused on AI architecture and cloud/SaaS strategy for Finastra’s Universal Banking business.
Responsibilities
Set the enterprise AI architecture vision, principles, standards, reference patterns, capability roadmaps, and technology strategy across multiple products, platforms, and business segments.
Provide authoritative architectural direction for generative AI, RAG, agentic AI, model integration, orchestration, prompt and context engineering, and AI evaluation.
Sponsor and lead strategic AI research, technology evaluations, and Proofs of Concept, translating validated outcomes into reusable, production‑grade capabilities with measurable business value.
Establish enterprise guardrails for responsible AI, security, privacy, model risk, data governance, observability, auditability, and human oversight in regulated environments.
Shape cloud‑native and SaaS architecture strategy for multi‑tenancy, tenant isolation, scalability, resilience, availability, metering, subscription models, and cost management.
Design, build, evaluate, and operationalize generative AI and RAG pipelines, multi‑agent workflows, and LLM evaluation in a Data Science & Machine Learning accelerator.
Compensation
Pay Rate: $45 per hour (C2C)
Responsibilities
Design and build secure multi‑agent workflows
Implement retrieval pipelines and metadata
Create evaluation datasets and metrics
Define and instrument technical and user‑centered evaluation
Work in two‑week agile sprints
Requirements
Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field
Strong hands‑on expertise in Python and end‑to‑end AI/ML model development, including data preparation, feature engineering, training, evaluation, optimization, and production integration.
Compensation
Pay Range: $55-60/Hour on W2/C2C (All Inclusive)
Responsibilities
Analyze business and technical requirements and design scalable AI/ML solutions aligned with enterprise architecture, security, privacy, and responsible AI standards.
Develop, train, evaluate, tune, and document machine learning, deep learning, NLP, and Generative AI models using Python, TensorFlow, and/or PyTorch.
Design and implement LLM‑based applications and Retrieval‑Augmented Generation pipelines using embeddings, vector databases, prompt engineering, orchestration frameworks, and appropriate evaluation methods.
Collaborate with data engineering, application, cloud, DevOps, QA, architecture, product, and business teams to integrate models into enterprise platforms through APIs and microservices.
Implement production‑readiness practices including automated testing, CI/CD, containerization, model versioning, monitoring, observability, drift detection, performance optimization, troubleshooting, and continuous improvement.
Forward‑deployed AI Engineer responsible for developing, deploying, and maintaining machine learning and generative AI solutions across business functions.
Responsibilities
Develop, train, evaluate, and deploy machine learning models
Build generative AI and LLM solutions using LangChain, LangGraph, CrewAI, AG2
Design and maintain scalable data pipelines
Implement real‑time and batch data ingestion and processing
Deploy AI solutions with Flask, FastAPI, Docker
Requirements
Bachelor’s or master’s degree in computer science, engineering, mathematics, statistics, or related discipline
Nice to have: Healthcare
Nice to have: insurance
Nice to have: third party administration
Nice to have: certifications in machine learning, AI, cloud platforms, data engineering
Partner with technical sales teams to differentiate Google Cloud to customers, serving as a technical expert for AI solutions.
Locations (2)
Singapore, Singapore
Bangkok, Bangkok, Thailand
Responsibilities
Drive the technical solution for complex workloads within AI product areas to ensure rapid and successful adoption
Combine business strategies and direct development and prototyping to provide functional, customer‑tailored solutions that secure buy‑in from customer domain experts
Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships
Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go‑To‑Market team
Work within product and engineering management systems to document, prioritize and drive resolution of customer feature requests and issues
Design, develop, and deliver production-ready AI solutions for clients while maintaining hands‑on engineering involvement.
Compensation
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current range is $102,400.00 - $204,100.00 per year.
Responsibilities
Architect end‑to‑end AI solutions including generative AI, agentic systems, and RAG
Lead solution architecture for AI build and proof‑of‑concept engagements
Remain hands‑on across solution development, coding, data integration, and debugging
Design and implement cloud‑native AI solutions on Azure, AWS, and GCP
Define architecture and integration patterns for LLMs, vector databases, APIs, microservices
Requirements
Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field
Nice to have: Master's degree in a technical field
Nice to have: cloud or architecture certifications
Nice to have: experience with OpenAI, Anthropic, Google LLMs
Nice to have: experience designing evaluation frameworks for LLMs
If performed in any of the following locations: DEU – Home Based – Berlin; DEU Home Based – Merseburg; DEU Home Based – Bad Soden; Germany – Berlin (Leipziger Platz); Germany – Düsseldorf (LexisNexis); Germany – Karlsruhe; Germany – Merseburg; Germany – Bonn; Germany – Kusterdingen; Germany – DUS – Johannstrasse; Home Based – Baden‑Württemberg; Home Based – Bremen; Home Based – Lower Saxony; Home Based – North Rhine‑Westphalia; or Home Based – Rhineland‑Palatinate, the base pay range is €86,700 - €144,400.
Responsibilities
Own product strategy and roadmap for intelligence capabilities
Work closely with data scientists, engineers, architects and patent experts
Set KPIs and report progress
Champion evaluation‑driven development
Track state of the art in AI and retrieval
Requirements
Bachelor's degree in computer science, engineering, a scientific subject or related field; master’s degree is a plus
Bachelor's degree in a technical field or equivalent practical experience
Nice to have: experience in developing agents using frameworks such as LangGraph, Semantic Kernel, or the Google AI Agent Development Kit
Nice to have: experience with cloud technologies including SaaS applications, iPaaS, business automation solutions, cloud infrastructure, Agentic AI, and cloud networking
Nice to have: experience engaging with, or presenting to, technical stakeholders or executive leaders
Nice to have: knowledge of integration patterns using OpenAPI and Model Context Protocol
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