GenAI Solutions Architect

Duration: 12-month contract (with potential for extension or full-time conversion)
Work Arrangement: Hybrid (1 or 2 days remote possible, preference for 4 or 5 days onsite)
Interview Process:
1st Round: 15-minute video interview via Microsoft Teams
2nd Round: In-person interview

Job Overview:
We are seeking a Senior GenAI Solutions Architect to lead the design and implementation of Generative AI-based applications within our enterprise ecosystem. This is a hands-on architecture role requiring a deep understanding of GenAI technologies, AI/ML systems, and data engineering best practices. You will work closely with stakeholders, business analysts, technology leaders, and development teams to conceptualize, design, and deliver robust GenAI solutions across a range of use cases.

Key Responsibilities:
Lead architecture design for GenAI-based applications and platforms.
Collaborate with cross-functional teams to define scalable, production-ready AI/ML solutions.
Integrate LLMs and agent-based models into existing and new applications.
Identify the right models, vector databases, and technologies for specific use cases.
Provide architectural guidance on implementing observability, monitoring, and traceability within GenAI solutions.
Contribute to POCs and platform development, such as GenAI gateways.
Serve as a key influencer in architectural decision-making across technical and business teams.

Must-Have Qualifications:
Proven experience implementing multiple GenAI projects.
5 6+ years of experience in AI/ML solutioning.
Strong hands-on experience in Python (required); R is a plus.
Experience with data engineering and building ML pipelines.
Expertise with AWS services such as ECS, EKS, databases, etc.
Solid background in AWS Solution Architecture, particularly in GenAI contexts.
Experience using and integrating LLMs, agents, and newer paradigms like agent-to-agent (A2A) and Multi-Component Prompting (MCP).
Strong communication and stakeholder management skills.
Experience with architectural observability, auditability, and traceability best practices.

Nice-to-Have Qualifications:
Prior experience as an Application Architect transitioning into an AI/ML Solutions Architect.
Exposure to NLP use cases.
Experience in platform-level architectural engineering (e.g., GenAI platform or gateway design).

This is an excellent opportunity for a GenAI architect who is passionate about shaping next-gen AI solutions and platforms while working with cutting-edge technologies in a collaborative and high-impact environment.