AI Engineer – Solution Architect

Agentic AI | Generative AI | AI Solution Architecture

We are looking for a hands-on AI Engineer – Solution Architect to design and deliver enterprise grade Agentic and Generative AI solutions. In this role, you will own the architecture of intelligent,

autonomous systems from concept to production, working closely with clients, business stakeholders, and engineering teams to turn complex business problems into scalable, secure, and reliable AI solutions.

If you are passionate about building AI systems that reason, plan, and act, and you have the architectural depth to take them beyond demos into real-world production, we would love to hear from you.

Key Responsibilities

Architect and design end-to-end AI/ML, Generative AI, and Agentic AI solutions on Azure,

Databricks, or AWS, combining platform-native AI services with custom-built components.

Design single-agent and multi-agent systems that are reliable, scalable, and cost-efficient in production.

Translate business requirements into solution architectures, reference designs, and technical roadmaps (HLD/LLD).

Lead the journey from proof-of-concept to production, including deployment, monitoring, and continuous improvement.

Define frameworks to measure, evaluate, and improve the quality and performance of AI systems.

Establish best practices for AI security, safety, governance, and Responsible AI.

Evaluate emerging AI technologies, frameworks, and protocols, and recommend the right fit for each use case.

Partner with clients and pre-sales teams on solutioning, technical workshops,



and proposals.

Mentor engineers and promote engineering excellence across AI delivery teams.

Core Skills & Expertise

AI Solution Architecture on Hyperscaler Platforms – architecting AI/ML, GenAI, and Agentic AI solutions on Azure, Databricks, or AWS using both platform-native AI services and fully custom-built architectures

Agentic AI System Design

Multi-Agent Orchestration

Generative AI & LLM Engineering

Context & Memory Engineering

Knowledge Retrieval Systems

Agent Tooling & Interoperability Protocols

AI Evaluation & Quality Engineering

LLMOps / AgentOps & Observability

AI Security, Safety & Governance

Production-Grade AI Engineering – strong Python, APIs, cloud-native and containerized deployments, Infrastructure as Code

Solution Leadership & Client Consulting

Required Qualifications

4 to 8 years of experience in AI/ML, including 4+ years designing and architecting Generative

AI and Agentic AI solutions.

Proven experience as the Solution Architect for AI/ML, GenAI, and Agentic AI solutions on

Azure, Databricks, or AWS, spanning both platform-native AI services and custom-built solutions.



Experience limited to cloud infrastructure architecture will not be considered a match.

Has designed and delivered GenAI or agentic / multi-agent solution in production in an enterprise environment, beyond PoCs and demos.

Hands-on ownership of architecture decisions across the full AI solution stack, including models, retrieval, agents, evaluation, security, and operations.

Solid problem-solving ability, with the judgement to balance accuracy, latency, cost, and risk in AI design.

Excellent communication skills, with the ability to explain complex AI concepts to technical and business audiences.

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Good to Have

AI, ML, or GenAI certifications on Azure, Databricks, or AWS.

Experience in client-facing consulting, pre-sales, or technical leadership roles.

Contributions to open-source AI projects, technical blogs, or community talks.

Exposure to multimodal AI and industry-specific AI use cases.

What We Offer The opportunity to architect cutting-edge Agentic AI solutions for leading enterprises.

Work with the latest AI platforms, models, and frameworks.

A collaborative, innovation-driven culture with strong learning and certification support.

Competitive compensation and clear career growth paths.

How to Apply

Apply directly via LinkedIn or share your updated resume at [email address]. Please include a brief note on a GenAI or agentic AI solution you personally architected, including your role, the platform used, and what reached production.

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