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Principal Architect @ Cognizant

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Cognizant  Principal Architect

Job Description



Job Summary

Principal Architect - LLM Agents and Multi-Agent Frameworks


Responsibilities

Summary

We are looking for a visionary Principal Architect to lead the design development and deployment of AI-powered solutions. This role is crucial in architecting intelligent agents and multi-agent frameworks using the latest advancements in Large Language Models (LLMs). The ideal candidate will have over 14 years of software engineering experience with at least 5 years focused on AI/ML. They will possess deep expertise across the full stack including frontend frameworks and backend technologies like Node.js and Python and cloud platforms such as AWS Azure or GCP. Responsibilities include leading architectural design integrating AI agents with core systems developing APIs and collaborating with data scientists to fine-tune LLMs. The role also involves establishing ML Ops practices designing data pipelines and mentoring junior engineers. Strong problem-solving skills excellent communication and a passion for continuous learning are essential.

Responsibilities

Lead Architectural Design

Define and evolve the overall architecture for LLM-powered agents and multi-agent systems that optimize agent economics over time

Design and implement robust scalable and maintainable microservices architectures

Ensure seamless integration of AI Agents with other core systems and databases

Oversee the development of APIs and SDKs for internal and external consumption

Model Building and Fine-tuning

Collaborate with data scientists and ML engineers to fine-tune and optimize LLMs for specific tasks and domains

Hands-on experience with agent frameworks like Autogen AWS Agent Framework LangGraph etc

Develop and implement robust model evaluation and monitoring systems such as Datadog LangSmith etc

Stay abreast of the latest advancements in LLM research and development

Prompt Engineering and LLM Integration

Develop and refine effective prompting strategies to maximize the performance of LLMs

Design and implement mechanisms for safe and reliable LLM integration

Address challenges related to bias hallucinations and other potential LLM limitations

ML Ops and Observability

Establish and maintain robust ML Ops practices including CI/CD pipelines model versioning and experiment tracking

Implement comprehensive monitoring and observability solutions to track model performance identify anomalies and ensure system stability

Data Engineering

Design and implement data pipelines for efficient data ingestion transformation and storage

Ensure data quality and security throughout the data lifecycle

Full-Stack Expertise

  • Frontend (optional): React Angular Vue.js or similar frameworks
  • Backend: Node.js Python (with frameworks like Flask Django or FastAPI) Java or other relevant languages
  • Database: SQL (MySQL PostgreSQL) NoSQL (MongoDB Cassandra) and experience with database design optimization and management
  • Cloud Platforms: Any 2 out of AWS Azure GCP (experience with serverless computing containerization and cloud-native technologies is a must)
  • Team Leadership and Mentorship

    Guide and mentor junior engineers in best practices for development and deployment of agents

    Foster a culture of innovation collaboration and continuous learning within the team


    Qualifications

  • Proven Experience: 14+ years of experience in software engineering with a strong focus on AI/ML for at least 5 years
  • Deep LLM Expertise: Demonstrated expertise in building and deploying applications powered by LLMs (e.g. Open AI Claude 3.5)
  • Architectural Skills: Proven ability to design and implement complex scalable and maintainable architectures. Proven experience on building systems using Distributed System Architecture principles is mandatory
  • Data Engineering Skills: Experience with data pipelines data warehousing and data analysis
  • ML Ops and Observability: Experience with ML Ops best practices including CI/CD model versioning and monitoring
  • Full-Stack Proficiency: Strong hands-on experience with frontend backend and cloud technologies
  • Communication and Collaboration: Excellent communication collaboration and leadership skills
  • Strong Problem-Solving and Analytical Skills: Ability to analyze complex problems and develop innovative solutions
  • Continuous Learning: Passion for learning and staying up to date with the latest advancements in AI/ML

  • Certifications Required

    AI ML certification preferred

    Job Classification

    Industry: IT Services & Consulting
    Functional Area / Department: Engineering - Software & QA
    Role Category: Software Development
    Role: Technical Architect
    Employement Type: Full time

    Contact Details:

    Company: Cognizant
    Location(s): Mumbai

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    Keyskills:   continuous integration analytical ci/cd artificial intelligence sql cloud containerization java leadership backend software engineering mongodb communication skills ml cd python serverless aiml front end framework node.js django collaboration system architecture aws flask

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