The AI Solution Lead will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices.

The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.

Key Responsibilities

AI Solution & Design

• Design and deliver enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
• Define designs for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
• Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
• Ensure scalability, reliability, and performance of deployed AI solutions.

Machine Learning & Model Expertise

• Provide deep technical expertise in:
• Large Language Models (LLMs)
• Transformer architectures
• Generative AI techniques
• Model evaluation and benchmarking
• Design approaches for fine-tuning, prompt engineering, and model adaptation.
• Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.

Production Deployment & MLOps

• Lead deployment of machine learning and GenAI systems into production environments.
• Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
• Ensure AI systems are secure, scalable, and operationally maintainable.

AI Governance & Responsible AI

• Implement frameworks for:
• AI governance
• Model explainability
• Transparency
• Risk management
• Ensure compliance with enterprise AI governance standards and regulatory expectations.
• Define policies for model validation, bias mitigation, and responsible deployment.

Client Engagement & Technical Leadership

• Act as a trusted technical advisor to client stakeholders.
• Clearly communicate complex AI concepts to executives, architects, and engineering teams.
• Represent the company with credibility in technical and strategic discussions around AI adoption.
• Work closely with client teams to translate business problems into AI-driven solutions.

Research & Innovation

• Stay current with emerging developments in:
• Generative AI
• Large language models
• AI agents and agentic architectures
• AI infrastructure and tooling
• Evaluate new research and technologies to determine their practical applicability in enterprise environments.
• Help shape the organization’s AI strategy and technical direction.

Required Qualifications

• Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
• Strong expertise in machine learning fundamentals and modern generative AI technologies.
• Proven experience designing and deploying AI/ML systems in production environments.
• Deep knowledge of:
• Large Language Models
• Generative AI architectures
• ML pipelines and model lifecycle management
• Experience working with AI frameworks and ecosystems used for building GenAI applications.
• Experience implementing AI governance, explainability, and responsible AI practices.
• Strong understanding of enterprise software architecture and distributed systems.

Preferred Qualifications

• Experience with agentic AI systems and orchestration frameworks.
• Experience building RAG-based AI systems.
• Familiarity with AI platform engineering and scalable AI infrastructure.
• Contributions to AI research, open-source projects, or technical publications.
• Experience working with enterprise clients in regulated industries.

Key Skills

Technical Skills

• Machine Learning & Data Science
• Large Language Models (LLMs)
• Generative AI systems
• AI agents and agentic framework
• MLOps and model lifecycle management
• AI governance and explainability

Professional Skills

• Strong analytical and problem-solving capabilities
• Excellent communication and presentation skills
• Ability to simplify complex AI concepts for diverse audiences
• Collaborative mindset and ability to work effectively within teams
• Client-facing professionalism and credibility

Work Environment

• Full-time in-office role with collaboration across engineering and client teams.
• Weekly client visits for workshops and solution design sessions.
• High collaboration with data scientists, engineers, architects, and business stakeholders.

What Success Looks Like in This Role

• Successfully designed and deliver production-grade AI systems.
• Become a trusted AI advisor to both internal teams and client stakeholders.
• Ensure responsible and governed adoption of AI technologies.
• Help organizations translate GenAI innovation into real operational value.

Job Title:

The AI Solution Lead will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices. 

The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.

Key Responsibilities

AI Solution & Design

• Design and deliver enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
• Define designs for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
• Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
• Ensure scalability, reliability, and performance of deployed AI solutions.

Machine Learning & Model Expertise

• Provide deep technical expertise in:
• Large Language Models (LLMs)
• Transformer architectures
• Generative AI techniques
• Model evaluation and benchmarking
• Design approaches for fine-tuning, prompt engineering, and model adaptation.
• Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.

Production Deployment & MLOps

• Lead deployment of machine learning and GenAI systems into production environments.
• Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
• Ensure AI systems are secure, scalable, and operationally maintainable.

AI Governance & Responsible AI

• Implement frameworks for:
• AI governance
• Model explainability
• Transparency
• Risk management
• Ensure compliance with enterprise AI governance standards and regulatory expectations.
• Define policies for model validation, bias mitigation, and responsible deployment.

Client Engagement & Technical Leadership

• Act as a trusted technical advisor to client stakeholders.
• Clearly communicate complex AI concepts to executives, architects, and engineering teams.
• Represent the company with credibility in technical and strategic discussions around AI adoption.
• Work closely with client teams to translate business problems into AI-driven solutions.

Research & Innovation

• Stay current with emerging developments in:
• Generative AI
• Large language models
• AI agents and agentic architectures
• AI infrastructure and tooling
• Evaluate new research and technologies to determine their practical applicability in enterprise environments.
• Help shape the organization’s AI strategy and technical direction.

Required Qualifications

• Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
• Strong expertise in machine learning fundamentals and modern generative AI technologies.
• Proven experience designing and deploying AI/ML systems in production environments.
• Deep knowledge of:
• Large Language Models
• Generative AI architectures
• ML pipelines and model lifecycle management
• Experience working with AI frameworks and ecosystems used for building GenAI applications.
• Experience implementing AI governance, explainability, and responsible AI practices.
• Strong understanding of enterprise software architecture and distributed systems.

Preferred Qualifications

• Experience with agentic AI systems and orchestration frameworks.
• Experience building RAG-based AI systems.
• Familiarity with AI platform engineering and scalable AI infrastructure.
• Contributions to AI research, open-source projects, or technical publications.
• Experience working with enterprise clients in regulated industries.

Key Skills

Technical Skills

• Machine Learning & Data Science
• Large Language Models (LLMs)
• Generative AI systems
• AI agents and agentic framework
• MLOps and model lifecycle management
• AI governance and explainability

Professional Skills

• Strong analytical and problem-solving capabilities
• Excellent communication and presentation skills
• Ability to simplify complex AI concepts for diverse audiences
• Collaborative mindset and ability to work effectively within teams
• Client-facing professionalism and credibility

Work Environment

• Full-time in-office role with collaboration across engineering and client teams.
• Weekly client visits for workshops and solution design sessions.
• High collaboration with data scientists, engineers, architects, and business stakeholders.

What Success Looks Like in This Role

• Successfully designed and deliver production-grade AI systems.
• Become a trusted AI advisor to both internal teams and client stakeholders.
• Ensure responsible and governed adoption of AI technologies.
• Help organizations translate GenAI innovation into real operational value.

Summary:

• Full stack Developer with 5+ years of experience in Angular 10+, TypeScript, .NET Core, C#, Azure SQL
• Proficiency working in Angular SPA applications
• Experience in Server-side technologies like .Net Core to build RESTful web services
• Experience working with Azure cloud technologies and services.
• Experience delivering serverless cloud solutions using PAAS model
• Experience using Azure App Service, Azure SQL, Service Bus, API Gateway Management, etc.
• Experience writing SQL Stored Procedures, Functions and ability to troubleshoot performance issue with SQL queries.
• Exposure to Microservices design patterns like pub/sub messaging, synchronous/asynchronous communication, etc.
• Experience with distributed version control systems Azure DevOps/Git
• Any Azure cloud certification from Microsoft preferred
• Experience or exposure to Agile development methodology
• Act with integrity, professionalism, and personal responsibility to uphold the firm’s respectful and courteous work environment.

The Senior Solution Architect will be responsible for leading the end-to-end architecture, design, and delivery of scalable, secure, and cloud-native applications aligned with client program objectives. This role requires strong hands-on technical expertise across full-stack development, cloud platforms, application integration, and modern AI-driven architectures, along with the ability to collaborate across business and technology stakeholders.

• Lead architecture design and implementation of enterprise-grade applications aligned with client business objectives and program goals.
• Define and govern solution architecture across backend, frontend, integration, security, and cloud layers to ensure scalability, performance, and quality.
• Collaborate with cross-functional teams including product owners, engineering, security, data, and infrastructure teams to deliver integrated solutions.
• Oversee backend and frontend web development, ensuring adherence to coding standards, best practices, and architectural guidelines.
• Drive application integration patterns, API strategies, and security enhancements, including identity and access management.
• Ensure alignment of development strategies, technical roadmaps, and architectural decisions with overall client program objectives.
• Conduct requirements gathering, translate business needs into technical solutions, and produce clear technical and architectural documentation.
• Oversee solution delivery, providing technical leadership, design reviews, and guidance throughout the development lifecycle.
• Design and enable solutions that leverage generative AI and agentic AI workflows, ensuring architectural compatibility, scalability, and responsible use.
• Provide thought leadership on emerging technologies, cloud-native patterns, and AI-driven solution design.

Technical Skills

• Hands-on expertise in .NET Full Stack Development.
• Strong proficiency in Angular Framework for frontend web development.
• Solid experience in Backend and Frontend Web Development with scalable design patterns.
• Strong understanding of Application Integration (APIs, messaging, services) and Security best practices.
• Hands-on knowledge of Microsoft Entra (Azure AD) for identity, authentication, and authorization.
• Experience integrating AI agentic workflows into enterprise applications.
• Strong knowledge of Microsoft Azure Cloud, including cloud-native architectures and services.
• Demonstrated experience with Cloud & Virtualization technologies.
• Good understanding of Data Architecture, including data modeling, data flows, and governance considerations.
• Familiarity with designing and implementing scalable systems leveraging Generative AI technologies.

Domain & Additional Experience

• Background or understanding of Accounting & Auditing concepts and processes is a strong plus.
• Experience working in complex enterprise environments with multiple stakeholders.
• Ability to balance hands-on technical work with architectural governance and strategic thinking.

The Senior Solution Architect will be responsible for leading the end-to-end architecture, design, and delivery of scalable, secure, and cloud-native applications aligned with client program objectives. This role requires strong hands-on technical expertise across full-stack development, cloud platforms, application integration, and modern AI-driven architectures, along with the ability to collaborate across business and technology stakeholders.

• Lead architecture design and implementation of enterprise-grade applications aligned with client business objectives and program goals.
• Define and govern solution architecture across backend, frontend, integration, security, and cloud layers to ensure scalability, performance, and quality.
• Collaborate with cross-functional teams including product owners, engineering, security, data, and infrastructure teams to deliver integrated solutions.
• Oversee backend and frontend web development, ensuring adherence to coding standards, best practices, and architectural guidelines.
• Drive application integration patterns, API strategies, and security enhancements, including identity and access management.
• Ensure alignment of development strategies, technical roadmaps, and architectural decisions with overall client program objectives.
• Conduct requirements gathering, translate business needs into technical solutions, and produce clear technical and architectural documentation.
• Oversee solution delivery, providing technical leadership, design reviews, and guidance throughout the development lifecycle.
• Design and enable solutions that leverage generative AI and agentic AI workflows, ensuring architectural compatibility, scalability, and responsible use.
• Provide thought leadership on emerging technologies, cloud-native patterns, and AI-driven solution design.

Technical Skills

• Hands-on expertise in .NET Full Stack Development.
• Strong proficiency in Angular Framework for frontend web development.
• Solid experience in Backend and Frontend Web Development with scalable design patterns.
• Strong understanding of Application Integration (APIs, messaging, services) and Security best practices.
• Hands-on knowledge of Microsoft Entra (Azure AD) for identity, authentication, and authorization.
• Experience integrating AI agentic workflows into enterprise applications.
• Strong knowledge of Microsoft Azure Cloud, including cloud-native architectures and services.
• Demonstrated experience with Cloud & Virtualization technologies.
• Good understanding of Data Architecture, including data modeling, data flows, and governance considerations.
• Familiarity with designing and implementing scalable systems leveraging Generative AI technologies.

Domain & Additional Experience

• Background or understanding of Accounting & Auditing concepts and processes is a strong plus.
• Experience working in complex enterprise environments with multiple stakeholders.
• Ability to balance hands-on technical work with architectural governance and strategic thinking.

Title- Devops Manager

Leadership & Strategy

• Lead and manage a global deployment engineering organization of 100+ resources across multiple shifts, ensuring round-the-clock operational coverage.
• Define and execute the strategic roadmap for deployment engineering, with a focus on automation-first principles.
• Partner with senior leadership, cloud operations, and DevOps teams to align deployment strategies with organizational goals.

• Deployment & Operations

• Oversee deployments across Microsoft Azure regional clouds and country-specific environments while ensuring compliance with local regulations.
• Ensure robust tracking, monitoring, and incident response for deployment pipelines.
• Establish and maintain white-glove service standards for high-priority business functions.

• Technology & Automation

• Drive adoption of Terraform, Azure-native services, and CI/CD pipelines to standardize and streamline deployment processes.
• Define and implement automation strategies to minimize manual interventions and reduce deployment cycle times.
• Ensure deployments are resilient, repeatable, and auditable.

• Team Management

• Build, mentor, and retain a high-performing global engineering team with clear career growth paths.
• Implement best practices in workload management, performance monitoring, and shift coverage planning.
• Foster a culture of accountability, innovation, and continuous improvement.

• Governance & Compliance

• Define policies and frameworks for secure, compliant, and auditable deployments across multiple geographies.
• Partner with InfoSec and compliance teams to ensure adherence to regulatory requirements.