Hands-on Full Stack Lead Architect to lead the design and delivery of enterprise-scale digital platforms across cloud, data, and AI ecosystems.
Responsibilities
Lead architecture, design, and delivery of enterprise applications using Java, Spring Boot, Microservices, Angular/React, and Cloud-native technologies.
Define technology strategy and roadmap for application modernization, AI adoption, and platform engineering.
Design and implement scalable data solutions leveraging Snowflake, Databricks, and modern data lakehouse architectures.
Drive integration of AI/GenAI capabilities, including LLMs, RAG frameworks, AI Agents, and intelligent automation solutions.
Architect event-driven systems using Kafka, Solace, and distributed caching technologies.
Requirements
Nice to have: Banking / Financial Services experience
Architect, code, and lead the backend vision and full-stack execution of enterprise GenAI platforms, designing high-performance AI systems at the intersection of modern cloud-native development and cutting-edge AI.
Responsibilities
Design and build core GenAI platform components serving 180,000+ users with exceptional performance, reliability, and security across distributed systems
Implement complex features across the entire stack from Go microservices and document pipelines to React interfaces and real-time streaming architectures
Build production-grade LLM applications, architect vector databases, implement agentic capabilities, and optimize AI inference for performance and cost efficiency
Design observability solutions, lead incident response and blameless postmortems, build CI/CD pipelines, and ensure production excellence through comprehensive monitoring and alerting
Architect Kubernetes/OpenShift deployments, implement service mesh (Istio), drive infrastructure-as-code and GitOps workflows, and ensure security best practices at every layer
Requirements
Bachelor's degree in computer science, Software Engineering, or related technical field
Design, develop and deploy backend services with a focus on high availability, low latency and scalability.
Compensation
₹30LPA, plus benefits.
Responsibilities
Design, develop and deploy backend services with a focus on high availability, low latency and scalability
Architect Distributed Systems: Design and implement robust microservices using Golang and Django that can handle concurrent processing of high-volume research data
Optimize AI Workflows: Build and refine asynchronous task queues (using tools like Celery or Redis) to manage long-running AI inference tasks without impacting the responsiveness of the user-facing API
Database Performance: Design and maintain efficient schemas for both relational databases (PostgreSQL) and specialized storage (Vector databases for AI search)
Load Management: Implement caching strategies and rate-limiting to protect service integrity during traffic spikes from global enterprise customers
Requirements
Nice to have: Familiarity with DevOps practices (Docker, AWS, CI/CD)
Nice to have: Experience building scalable and distributed systems
Nice to have: Strong ownership mindset
Nice to have: Practical, solution-oriented thinker
Design, develop, and maintain backend services using Python, build and optimize RESTful APIs and microservices, and work with cloud platforms such as Microsoft Azure or GCP.
Responsibilities
Design, develop, and maintain backend services using Python
Build and optimize RESTful APIs and microservices
Work with Microsoft Azure (priority) or GCP to design, deploy, and manage cloud solutions
Implement CI/CD pipelines and automated testing workflows
Work with Docker and Kubernetes in production environments
Design, build, and deploy machine learning and generative AI solutions for healthcare, including conversational agents and cloud-native workflows.
Responsibilities
Design, build, and deploy machine learning and generative AI solutions—including conversational agents, natural language processing (NLP/NLU) services, and agentic workflows to solve complex healthcare challenges
Develop, evaluate, and optimize conversational voice and chat bots using platforms such as AWS Bedrock, Bedrock AgentCore, AWS Lex, or related agentic frameworks
Implement and integrate cloud-native AI infrastructure, utilizing AWS services such as Lambda, DynamoDB, S3, API Gateway, IAM, and CloudWatch
Apply enterprise-approved AI tools, Retrieval-Augmented Generation (RAG) patterns, vector databases, and model quantization/optimization techniques to deliver scalable, performant applications
Incorporate Responsible AI practices, guardrails, security controls, and prompt engineering techniques to ensure model accuracy, data privacy, and safe operational deployment
The AI Application Principal Technologist will lead the design and implementation of Agent-based capabilities within AVEVA's Engineering portfolio. This role is responsible for defining AI-native architectures, enabling multi-agent systems, and transforming existing product capabilities into intelligent services accessible through modern AI interaction models.
Responsibilities
Design and implement Agent-based capabilities within Engineering products.
Define AI-native product architectures and drive adoption of modern AI interaction patterns.
Transform existing product capabilities into Agent-ready and MCP-enabled service architectures.
Design and implement multi-agent systems to enhance product intelligence and automation.
Requirements
Bachelor's degree or above in Computer Science, Artificial Intelligence, or a related discipline
The VP, AI Security Architect Lead will define and drive the enterprise security architecture strategy for Artificial Intelligence, Generative AI, Machine Learning, and emerging AI technologies.
Compensation
The salary range for this position is 130,000.00 - 210,000.00 USD Annual and is eligible for an annual bonus based on individual and company performance.
Responsibilities
Define and execute the enterprise AI Security Architecture strategy, principles, standards, reference architectures, and guardrails.
Create reusable security patterns for Generative AI, copilots, Retrieval-Augmented Generation (RAG), model and inference APIs, autonomous or agentic AI, and enterprise AI platforms.
Lead security architecture assessments for high-impact AI solutions across cloud, SaaS, API, data, application, and enterprise technology environments.
Embed security-by-design across the AI lifecycle, including development, deployment, integration, monitoring, and retirement.
Establish an AI threat-modeling approach aligned with MITRE ATLAS and OWASP guidance, translating threats into actionable controls and engineering requirements.
Requirements
Bachelor's degree in Computer Science, Cybersecurity, Information Technology, Engineering, or a related discipline, or equivalent relevant experience
Design, build, and ship agentic AI solutions hands-on, turning validated solution designs into working agents and building reference implementations to accelerate production delivery.
Compensation
The annualized base pay for the advertised position, located in the specified area, ranges from a minimum of $130,000 to a maximum of $214,000. You may also have the opportunity to participate in discretionary equity (stock) based compensation and/or performance-based variable pay programs.
Responsibilities
Build multi-agent workflows across planner, retrieval, tool-calling, and validation steps
Implement autonomy boundaries, human-in-the-loop checkpoints, deterministic guardrails, and audit trails in code
Develop and integrate tools and services through Model Context Protocol (MCP) and enterprise APIs
Build retrieval pipelines over unstructured submissions, claims files, and financial records
Tune retrieval quality and grounding using measurable metrics such as hit rate, MRR, and citation accuracy
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field or equivalent experience
Design and deliver enterprise‑grade Agentic AI architectures built on LLMs, multi‑agent systems, and orchestration layers.
Locations (2)
Charlotte, North Carolina, United States
Somerset, New Jersey, United States
Compensation
The annual salary for this position will be between $104,000 to $166,000 per year depending on the experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program and stock awards, based on performance and subject to the terms of Cognizant’s applicable plans.
Responsibilities
Define end‑to‑end Agentic AI architecture frameworks leveraging LLMs, multi‑agent systems, and orchestration layers.
Design autonomous AI agents capable of planning, reasoning, memory management, and tool usage.
Establish reference architectures for enterprise‑grade AI applications that are cloud‑native, scalable, and secure.
Integrate AI agents with enterprise systems, including data platforms, ERP, CRM, APIs, and event‑driven systems.
Apply Claude Code expertise to design and deliver AI‑driven solutions.
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