ThinkPalm - AI Solution Architect

Job Title : AI Solution Architect

Experience :

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 :

- Lead development of AI-powered applications using :

1. LLM frameworks (LangChain, LlamaIndex, etc.)

2. OpenAI / open-source models (LLaMA, Mistral, etc.)

- Build and optimize :

1. Prompt engineering strategies

2. Retrieval-Augmented Generation (RAG)

3. 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 :

1. RPA (UiPath, Automation Anywhere)

2. Workflow orchestration tools

3. 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 :

1. Machine Learning & Deep Learning concepts

2. Generative AI, Large Language Models (LLMs) , SLMs.

- Experience with :

1. RAG pipelines, embeddings, vector databases (Pinecone, FAISS, Weaviate)

2. Cloud platforms : AWS / Azure / GCP (AI services, MLOps)

3. API design, microservices architecture, and distributed systems

- Hands-on with :

1. LangChain / LlamaIndex / Semantic Kernel

2. Model deployment and MLOps pipelines

- Familiarity with :

1. Data engineering pipelines and big data ecosystems

AI Tools & Ecosystem :

- Expertise in modern AI tools including :

1. AI coding assistants (Copilot, cursor, windsurf, ChatGPT, etc.)

2. Automation platforms (RPA + AI integration)

3. 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 :

- Bachelor's/Master's 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