Thinkpalm Technologies
AI Solution Architect
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Kochi, Kerala, India
Work mode:
Onsite
Published on:
7 August 2026
What they need
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
- Lead development of AI-powered applications using:
- LLM frameworks (LangChain, LlamaIndex, etc.)
- OpenAI / open-source models (LLaMA, Mistral, etc.)
- 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 .
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