Architect – Generative AI

Lovelytics is seeking a Generative AI Architect with hands-on experience delivering client-facing projects in the Generative AI domain, particularly on the Databricks platform. As part of our growing AI & GenAI practice, this role offers an exciting opportunity to design and deploy state-of-the-art solutions that combine language models, vector databases, and cutting-edge orchestration frameworks.

We’re looking for a GenAI Architect who's already taken GenAI from concept to production on Databricks. Joining our GenAI practice means you’ll architect, design, and deploy solutions that work in the real world: RAG pipelines, LLM orchestration, vector search, AI agents and the architecture decisions that make all of it scale. This isn't a research role, it's for practitioners who've worked with clients, understood their problem, and built something to solve it. If you're energized by the pace of this space and want to work alongside people who take data and AI seriously, we'd love to talk.

Note: This position is not eligible for work sponsorship at this time.

Primary Responsibilities:

• Own end-to-end architecture and technical strategy for complex GenAI and Agentic AI solutions on the Databricks Data Intelligence Platform, from discovery through production.
• Serve as the senior technical advisor to client stakeholders, translating business problems into scalable AI architectures and implementation roadmaps.
• Design solutions across Agentic AI, Compound AI, LLMs, evaluation, optimization, governance, observability, and production AI engineering using relevant Databricks capabilities.
• Provide technical leadership across multiple project teams, ensuring architectural quality, engineering standards, security, scalability, Unity Catalog governance, and production readiness.
• Guide and mentor Senior, Lead and Principal GenAI engineers and consultants, strengthening both GenAI and Databricks technical capabilities across the practice.
• Lead technical discovery, estimation, architecture, proposals, demos, and pre-sales activities for strategic Databricks GenAI opportunities.
• Develop reusable Databricks reference architectures, accelerators, patterns, and best practices for enterprise GenAI and Agentic AI implementations.
• Stay current on emerging Databricks AI capabilities and broader GenAI technologies, translating them into practical client solutions.
• Build strong client relationships, identify expansion opportunities, and help grow large, durable Databricks AI accounts.
• Contribute to Databricks and GenAI thought leadership through workshops, blogs, conference sessions, demos, and internal enablement.

Our Ideal Candidate's Skills and Experiences:

• B.S. in Computer Science or equivalent technical field.
• 10+ years of technology experience, including significant experience in data, ML, AI, or cloud architecture.
• 2-3 years of meaningful hands-on GenAI/LLM experience preferred, with demonstrated production implementations.
• Proven experience as a Solution Architect, AI Architect, Lead Engineer, or equivalent technical leadership role.
• Demonstrated experience leading complex client engagements and multiple technical workstreams.
• Prior consulting or professional services experience strongly preferred.
• Experience mentoring and technically leading teams required. Formal people-management experience is valuable but not required
• Deep hands-on experience designing and delivering production GenAI and Agentic AI solutions.
• Strong understanding of LLMs, AI agents, agent orchestration, tool use, Compound AI systems, evaluation, prompt optimization, and LLMOps.
• Strong Databricks experience, including Mosaic AI capabilities, Model Serving, MLflow, Unity Catalog, Databricks Apps, Vector Search, and Lakehouse architecture.
• Ability to design secure, scalable, governed enterprise AI architectures integrating structured and unstructured data.
• Strong Python and software engineering fundamentals, including APIs, distributed systems, CI/CD, testing, and production deployment patterns.
• Experience with model evaluation, observability, guardrails, performance optimization, and cost management.
• Working knowledge of classical ML and how GenAI, ML, data engineering, and analytics fit into broader AI solutions.
• Strong client-facing consulting and executive communication skills.

Nice-to-Have Skills and Experiences:

• Advanced Databricks certifications and strong familiarity with the broader Databricks Data Intelligence Platform.
• Experience with DSPy, GEPA, automated prompt optimization, fine-tuning, synthetic data generation, and advanced evaluation techniques.
• Experience building multi-agent systems, MCP-based integrations, tool-calling architectures, and human-in-the-loop workflows.
• Familiarity with multiple foundation model providers and model-selection strategies across proprietary and open-source models.
• Experience with cloud platforms such as Azure, AWS, or GCP, particularly enterprise security, networking, and identity integration.
• Experience with traditional ML, MLOps, feature engineering, and predictive modeling in addition to GenAI.
• Familiarity with industry-specific AI patterns in Financial Services, Healthcare, Manufacturing, Energy, Retail, Telecom, or other enterprise sectors.
• Experience managing or mentoring senior technical resources such as Principals, Leads, and Engineers.
• Experience participating in pre-sales, RFPs, proposals, solution estimation, and executive presentations.
• Previous experience building or scaling an AI/GenAI practice, Center of Excellence, or technical community.

What We Promise You:

• Meaningful, cutting-edge projects in Generative AI with clients across industries—from Fortune 100 firms to disruptive startups.
• Rapid learning and mentorship opportunities with AI/GenAI thought leaders and practitioners.
• A culture of experimentation, innovation, and continuous improvement.
• Opportunity to be a conference speaker, blogger, writer. 
• A diverse, inclusive team and one of the best GenAI teams, where your voice, ideas contributions are highly valued.

The base salary range for this position for candidates based in the US is $160,000-210,000 per year. Compensation is determined based on a variety of factors including, but not limited to, relevant experience, skills, qualifications, scope of role and budget. Employees in Ontario, CA are paid using Canada market data in CAD. Candidates are not guaranteed to be placed at any particular point within the range, and most offers will fall within the middle of the range or below. Lovelytics is committed to pay equity and transparency in compensation practices.