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The Sr. Consultant, Microsoft AI Solutions drives end-to-end delivery success for assigned Microsoft Copilot and AI solution components. This includes leading solution design activities within engagement scope, aligning stakeholders on requirements and implementation approach, developing delivery-ready artifacts, and executing configuration, integration, and deployment tasks. The role ensures solutions meet security, governance, and operational standards and supports go-live readiness, stabilization, and handoff to operations teams. 

This role will also support presales and technical deep-dive sessions (on an as-needed basis) with customers prior to the initiation of delivery engagements, focused on solution feasibility, technical validation, and delivery readiness.

SUMMARY OF ESSENTIAL JOB FUNCTIONS:

Solution Envisioning and Business Alignment

• Lead and support AI solution envisioning activities with customers, including workshops, demonstrations, and technical deep-dive sessions.
• Translate business scenarios and use cases into conceptual solution designs - aligned to Microsoft AI products and services via Copilot, Azure, etc.
• Support technical feasibility and delivery readiness assessments prior to delivery initiation, validating platform fit, approach, and constraints.
• Facilitate alignment with customer stakeholders on solution scope, requirements, architecture approach, and success criteria.
• Develop conceptual designs and delivery-aligned solution definitions to guide successful implementation.

Solution Delivery and Execution

• Lead solution design activities within delivery engagements, translating approved concepts into functional and non-functional requirements.
• Configure, build, and implement Microsoft solutions through Microsoft Copilot, Copilot Studio, Power Platform, and supporting Azure services.
• Integrate Copilot solutions with Microsoft 365, Teams, Microsoft Foundry, and existing enterprise systems and workflows.
• Implement identity, security, governance, and access controls aligned to customer and organizational standards.
• Execute testing, validation, and troubleshooting to ensure solution quality and readiness for production use.
• Support deployment, go-live, and stabilization activities to ensure successful adoption.

Communication and Collaboration

• Ability to serve as the primary delivery lead for assigned solution components or workstreams within an engagement.
• Partner with solution architects and project managers to plan, execute, and track delivery milestones.
• Collaborate with customer technical and business teams to drive alignment, decision-making, and adoption throughout the engagement.
• Communicate delivery status, risks, and dependencies to internal and customer stakeholders.
• Support limited presales and technical deep-dive sessions (on an as-needed basis) to enable solution feasibility, technical validation, and delivery readiness.

Continuous Improvement and Delivery Excellence

• Develop and contribute to delivery artifacts including architecture workshop agendas, diagrams, configuration specifications, runbooks, deployment guides, and validation checklists.
• Capture, sanitize, and contribute reusable solution assets, patterns, and implementation guidance to internal repositories.
• Contribute feedback and lessons learned to improve delivery efficiency, consistency, and quality across similar engagements.
• Support initiatives focused on standardizing delivery approaches and accelerating future implementations.
• Stay current on Microsoft Copilot, Microsoft Foundry, and related platform updates to continuously improve delivery practices.

REQUIRED SKILLS AND EXPERIENCE:

·      Bachelor’s degree required; advanced degree or relevant certifications preferred.

·      8+ years of experience in consulting, enterprise architecture, or digital transformation with client-facing responsibilities.

·      Experience advising senior leaders on AI, Copilot, or cloud modernization initiatives.

·      Strong hands-on expertise with Microsoft Copilot and Copilot Studio.

·      Experience designing AI-enabled solutions / automations, or integrating with existing business processes leveraging Microsoft 365, Teams, and Azure services.

·      Strong understanding of Identity and Access Management design concepts for Microsoft Copilot and AI agents

·      Familiar with agent design patterns & data access patterns.

·      Familiar with Azure OpenAI, Azure AI Search, Logic Apps, Azure Functions, and integration architectures. Hands-on experience in integrating with one or more of these services through Copilot Studio is preferred.

·      Experience in leading and contributing to presales efforts including readiness assessments, envisioning workshops, and proposal development.

·      Microsoft certifications in Microsoft Copilot, Power Platform, Azure, and Microsoft AI are preferred.

·      Highly organized, detail-oriented, excellent time management skills, and able to effectively prioritize tasks in a fast-paced, high-volume, and evolving work environment.

·      Ability to approach customer requests with a proactive and consultative manner; listen to and understand user requests and needs, and effectively deliver.

·      Strong influencing skills to get things done and inspire business transformation.

·      Excellent oral, written communication, and presentation skills with an ability to present AI-related concepts to C-Level Executives and non-technical audiences.

·      Conflict negotiation and critical thinking skills and agility.

·      Ability to travel when needed.

1. Sr. Data Engineer:

 Core Skills – Data Engineering, Big Data, Pyspark, Spark SQL and Python

Candidate with prior Palantir Cloud Foundry OR Clinical Trial Data Model background is preferred

Major accountabilities:

• Responsible for Data Engineering, Foundry Data Pipeline Creation, Foundry Analysis & Reporting, Slate Application development, re-usable code development & management and Integrating Internal or External System with Foundry for data ingestion with high quality.
• Have good understanding on Foundry Platform landscape and it’s capabilities
• Performs data analysis required to troubleshoot data related issues and assist in the resolution of data issues.
• Defines company data assets (data models), Pyspark, spark SQL, jobs to populate data models.
• Designs data integrations and data quality framework.
• Design & Implement integration with Internal, External Systems, F1 AWS platform using Foundry Data Connector or Magritte Agent
• Collaboration with data scientists, data analyst and technology teams to document and leverage their understanding of the Foundry integration with different data sources - Actively participate in agile work practices
• Coordinating with Quality Engineer to ensure the all quality controls, naming convention & best practices have been followed

Desired Candidate Profile :

• Strong data engineering background
• Experience with Clinical Data Model is preferred
• Experience in
• SQL Server ,Postgres, Cassandra, Hadoop, and Spark for distributed data storage and parallel computing
• Java and Groovy for our back-end applications and data integration tools
• Python for data processing and analysis
• Cloud infrastructure based on AWS EC2 and S3
• 7+ years IT experience, 2+ years’ experience in Palantir Foundry Platform, 4+ years’ experience in Big Data platform
• 5+ years of Python and Pyspark development experience
• Strong troubleshooting and problem solving skills
• BTech or master's degree in computer science or a related technical field
• Experience designing, building, and maintaining big data pipelines systems
• Hands-on experience on Palantir Foundry Platform and Foundry custom Apps development
• Able to design and implement data integration between Palantir Foundry and external Apps based on Foundry data connector framework
• Hands-on in programming languages primarily Python, R, Java, Unix shell scripts
• Hand-on experience in AWS / Azure cloud platform and stack
• Strong in API based architecture and concept, able to do quick PoC using API integration and development
• Knowledge of machine learning and AI
• Skill and comfort working in a rapidly changing environment with dynamic objectives and iteration with users.

 Demonstrated ability to continuously learn, work independently, and make decisions with minimal supervision