Job description

About Us:

Solytics Partners is a Global Analytics firm, recognized with multiple industry awards for innovation and excellence. Our team comprises experts with deep domain knowledge in risk, analytics, AI/ML, AML/FCC, and fraud. By converging this expertise with cutting-edge technologies like AI, Machine Learning, Generative AI, and Large Language Models (LLMs), we deliver powerful automated platforms and incisive point solutions.

Our offerings enable clients to streamline and future-proof their risk, AML, and analytics processes, comply seamlessly with global regulations, and safeguard financial systems. Whether it’s solving complex challenges or driving operational efficiency, Solytics Partners is committed to empowering organizations with transformative tools to stay ahead in an evolving regulatory landscape.

Role Summary:

We are looking for a strong, hands-on AI Architect to define and drive the architecture of AI-powered products and solutions within a product engineering environment. The ideal candidate will have strong experience in AI/ML, Generative AI, LLMs, RAG, System Design, and Solution Architecture, with a proven track record of taking AI initiatives from business problem definition and PoCs through production deployment and scale.

This role will work closely with Product Managers, Data Scientists, AI/ML Engineers, and Engineering teams to translate business requirements into scalable, secure, high-performance AI solutions. The AI Architect will provide technical direction to a team of Data Science and AI/ML Engineers, establish architectural best practices, evaluate emerging AI technologies, and ensure that AI solutions are practical, production-ready, and aligned with product and business goals.

Key Responsibilities:

Understand complex business and product requirements and translate them into end-to-end AI/ML and GenAI solution architectures.
Own AI solution architecture and system design from concept through production.
Design scalable architectures covering models/LLMs, data pipelines, APIs, integrations, retrieval systems, cloud infrastructure, security, monitoring, and deployment.
Lead the development of PoCs, prototypes, and MVPs to validate AI use cases and establish technical feasibility.
Design and guide implementation of GenAI, RAG, LLM and Agentic AI solutions.
Work closely with Data Scientists and AI/ML Engineers to convert architectural designs into robust, production-ready implementations.
Provide technical leadership and architectural guidance to a team of 10+ AI/ML and Data Science engineers.
Review technical designs, identify architectural gaps, and drive engineering best practices across AI initiatives.
Make informed decisions around model selection, architecture patterns, technology choices, scalability, latency, reliability, and cost.
Design and implement integrations using APIs, microservices, and cloud-native architectures.
Ensure AI solutions meet organizational requirements around security, privacy, compliance, scalability, performance, and reliability.
Identify reusable AI components, frameworks, accelerators, and architecture patterns to improve engineering efficiency.
Evaluate emerging AI/GenAI technologies and assess their practical applicability to product use cases.
Create and maintain architecture diagrams, solution designs, technical documentation, and architecture decision records.
Partner with Product and Engineering leadership to define the technical roadmap for AI/GenAI capabilities.
Help take successful PoCs into production-grade, scalable AI products.

Must-Have Technical Skills:

AI Architecture & System Design

Proven experience designing end-to-end AI/ML or GenAI solutions.
Strong understanding of System Design, Solution Architecture, and architectural design patterns.
Experience translating business/product requirements into technical architecture.
Ability to make architecture and technology decisions independently.

GenAI / LLM / RAG:

Strong hands-on experience with Generative AI and LLM-based applications.
Solid experience designing and implementing RAG architectures.
Good understanding of embeddings, vector search/databases, retrieval, prompting, context management, and LLM integration.
Practical exposure to Agentic AI / AI Agents is highly desirable.
Experience with one or more relevant GenAI frameworks/platforms is expected.

Hands-on Engineering:

Strong Python programming experience.
Experience working with REST APIs, microservices, integrations, and distributed systems.
Ability to build and technically validate AI PoCs/MVPs.
Strong understanding of software engineering principles and production development practices.

Cloud & Production Architecture:

Strong experience with at least one major cloud platform: AWS, Azure, or GCP.
Experience designing and deploying cloud-native AI/ML solutions.
Experience taking AI solutions from PoC/MVP to production.
Understanding of scalability, performance, reliability, observability, deployment, and cost optimization.

Leadership & Collaboration:

Proven experience providing technical leadership to AI/ML or engineering teams.
Ability to mentor and guide Data Scientists, ML Engineers, and AI Engineers.
Strong communication skills with the ability to explain complex technical concepts to both technical and product/business stakeholders.
Comfortable working in a product-driven, fast-paced environment.
Strong problem-solving and decision-making skills.
Ability to balance technical excellence with business value, time-to-market, scalability, and cost.

What We Are Looking For:

We are looking for someone who has real-world ownership of AI architecture, not just exposure to AI technologies.

The ideal candidate should be able to demonstrate examples where they have:

Understood a business problem → designed the AI solution → created/led a PoC → made architecture decisions → guided engineering implementation → taken the solution to production → scaled and improved it.
Candidates with strong Senior AI Engineer / Lead AI Engineer / AI Solution Architect / AI Architect / GenAI Architect backgrounds are encouraged to apply, provided they have demonstrated hands-on architecture and production ownership.

Preferred Background:

6–8 years of overall experience in AI/ML, software engineering, or related technology roles.
Strong combination of hands-on engineering + AI expertise + architecture ownership.
Experience working in a product-based organization or building customer-facing/product-grade AI solutions is strongly preferred.
Experience working with cross-functional Product, Engineering, Data Science, and AI teams.
Proven experience delivering AI solutions that operate at production scale.

We are looking for a technically strong AI Architect who can design, build, challenge, guide, and scale real AI solutions while providing technical direction to a growing AI/ML engineering team.

Someone shared one job with you. ASAI keeps finding the rest.

Scored, not searched. Every role ranked against your actual profile.

Alerts as often as hourly. Reach new roles while the pile is still small.

Skill gaps, spelled out. See exactly which requirements you don't meet yet.

Verified jobs, only. Say no to ghost jobs. Your time deserves respect.