AI Solution Architect

We are looking for an AI Solution Architect with 12+ years in software engineering, solution architecture, or related roles, with at least 3 - 5 years of hands-on experience in AI/ML and GenAI-driven solutions.

Role Overview:

We are seeking a highly experienced AI Solution Architect to design, lead, and implement scalable, enterprise-grade AI solutions. The ideal candidate will have strong expertise in Generative AI, AI-assisted development (vibe coding), automation frameworks, and the ability to translate business problems into impactful AI-driven architectures.

This role requires a blend of technical depth, architectural thinking, and business acumen, with hands-on involvement in building AI-powered systems.

Key Responsibilities:

Solution Architecture & Design

• Design end-to-end AI/ML and Generative AI architectures for enterprise use cases.
• Define scalable, secure, and high-performance AI solution blueprints.
• Architect solutions leveraging LLMs, multi-agent systems, RAG pipelines, and vector databases.
• Integrate AI solutions with enterprise systems (ERP, CRM, data platforms, APIs).

AI & GenAI Implementation

1. Lead development of AI-powered applications using:

• LLM frameworks (LangChain, LlamaIndex, etc.)
• OpenAI / open-source models (LLaMA, Mistral, etc.)

2. Build and optimize:

• Prompt engineering strategies
• Retrieval-Augmented Generation (RAG)
• Fine-tuning and model customization.
• Ensure responsible AI practices (bias mitigation, explainability, governance).

AI-Assisted Development (Vibe Coding) & Automation

• Leverage tools like GitHub Copilot, Cursor, Windsurf, Gemini, ChatGPT, etc. to accelerate development.
• Drive AI-led coding practices, rapid prototyping, and developer productivity.
• Design intelligent automation solutions using:
• RPA (UiPath, Automation Anywhere)
• Workflow orchestration tools
• AI agents for process automation

Technology Leadership

• Evaluate and recommend emerging AI tools, frameworks, and platforms.
• Provide technical leadership and mentorship to engineering teams.
• Define best practices, coding standards, and reusable frameworks.

Stakeholder Engagement

• Work closely with BD team/Sales team/ business leaders to identify AI opportunities.
• Translate business requirements into technical AI solutions.
• Present architecture, PoCs, and solutions to senior stakeholders and customers.

Governance & Scalability

• Ensure compliance with enterprise security, privacy, and regulatory requirements.
• Design monitoring, observability, and performance optimization strategies for AI systems.

Required Skills & Competencies

Technical Skills

Strong programming expertise in Python (mandatory), and familiarity with Java/Node.js is a plus.

• Deep understanding of:
• Machine Learning & Deep Learning concepts
• Generative AI, Large Language Models (LLMs) , SLMs.
• Experience with:
• RAG pipelines, embeddings, vector databases (Pinecone, FAISS, Weaviate)
• Cloud platforms: AWS / Azure / GCP (AI services, MLOps)
• API design, microservices architecture, and distributed systems.

Hands-on with:

• LangChain/ LlamaIndex / Semantic Kernel
• Model deployment and MLOps pipelines

Familiarity with:

• Data engineering pipelines and big data ecosystems

AI Tools & Ecosystem

• Expertise in modern AI tools including:
• AI coding assistants (Copilot, cursor, windsurf, ChatGPT, etc.)
• Automation platforms (RPA + AI integration)
• Prompt engineering and evaluation tools
• Strong awareness of rapidly evolving AI landscape.

Soft Skills

• Excellent problem-solving and analytical thinking
• Strong communication and presentation skills
• Ability to work with cross-functional and global teams
• Strategic thinking with execution focus

Preferred Qualifications

• Bachelors/Masters degree in Computer Science, AI, Data Science, or related field
• Certifications in cloud (AWS/Azure/GCP) or AI/ML domains
• Experience in enterprise domains like Telecom, BFSI, Healthcare, or Retail
• Exposure to AI governance frameworks and ethical AI practices .