AIML Engineer

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.

Strong 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.