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Cognizant
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Lead Developer

Lead Developer

Cognizant

8 - 9 years

Bengaluru

Posted:15 hours ago

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Job Description

Job Summary

Technology Architect ETE124 will design and govern end to end solutions that combine Generative AI SAP SAC Analytics Prompt Engineering Agentic AI and Context Engineering in a hybrid work model. The role ensures scalable architectures robust delivery practices and strong alignment with customer outcomes for data driven and AI enhanced applications.

Responsibilities

Drive comprehensive architecture blueprints that integrate Generative AI services SAP SAC Analytics models Prompt Engineering workflows Agentic AI components and Context Engineering patterns to deliver secure and scalable enterprise solutions

Define reference architectures and standards that guide project teams in consistent adoption of Generative AI SAP SAC Analytics and related AI accelerators while ensuring alignment with enterprise strategy and compliance

Collaborate with product owners and business stakeholders to translate complex analytics and AI requirements into clear solution designs that optimize data flows latency and experience quality for end users

Guide engineering teams in designing context aware pipelines that harness structured and unstructured data ensuring that Context Engineering practices improve relevance precision and explainability of AI outcomes

Architect reusable Prompt Engineering patterns and guardrails that support safe and predictable use of large language models reducing experimentation risk and improving maintainability

Evaluate and select cloud native and on premises components for SAP SAC Analytics and Generative AI workloads balancing cost performance resilience and regulatory obligations for global enterprises

Oversee non functional architecture aspects including performance reliability observability security and privacy for AI centric and analytics centric solutions across development test and production environments

Coordinate with data engineering and integration teams to design robust ingestion transformation and semantic modeling layers that feed SAP SAC Analytics dashboards and AI driven insights with high data quality

Establish architecture review checkpoints document decisions and track technical debt ensuring that AI and analytics platforms remain extensible maintainable and ready for future innovation cycles

Mentor solution engineers and analysts in best practices for Prompt Engineering Agentic AI orchestration context management and SAP SAC Analytics modeling to build a strong internal capability base

Conduct feasibility assessments and proof of value experiments that demonstrate how Generative AI and Agentic AI solutions improve decision making productivity and customer satisfaction for clients and internal users

Partner with security and risk teams to embed responsible AI principles access controls data protection mechanisms and monitoring capabilities across Generative AI and analytics solutions

Align technology roadmaps with sustainability and social impact objectives by promoting architectures that improve operational efficiency reduce wasteful processing and democratize access to trustworthy insights for diverse stakeholders

Qualifications

Bring fifteen to eighteen years of progressive experience in architecture or senior technical design roles with a strong track record of delivering complex analytics and AI enabled solutions in large enterprises

Demonstrate deep hands on expertise in Generative AI technologies including large language models embeddings retrieval systems and prompt optimization combined with practical experience in Prompt Engineering and Agentic AI solutions

Possess advanced proficiency in SAP SAC Analytics including model design data actions planning scenarios visualization standards and integration with upstream data platforms and downstream enterprise applications

Show strong skills in Context Engineering including context store design session management grounding techniques and strategies for reducing hallucination risks in AI responses across multiple use cases

Exhibit solid knowledge of software engineering practices covering microservice architectures event driven patterns API design version control automated testing and observability tailored to AI centric workloads

Offer domain exposure to enterprise analytics and digital transformation programs in areas such as finance analytics operations analytics customer insights or supply chain analytics where AI augmented decisioning provides measurable value

Bring good to have exposure to industry specific regulations and practices across areas such as banking retail manufacturing or healthcare analytics to align AI and analytics solutions with domain expectations and controls

Work primarily in a hybrid work model combining on site collaboration with remote delivery while maintaining high levels of communication documentation quality and coordination with distributed teams

Operate in a day shift environment while remaining flexible to collaborate across time zones through planned overlap windows and asynchronous communication mechanisms where necessary

Require no regular travel while remaining open to limited short visits if later agreed under specific project needs and organizational guidelines

Skills Required

Digital Integration Architecture Cloud Enterprise Development Analytics Application

Work Mode

Work from Office

Job Type

Full Time

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Lead Developer