Overview

BTVK Advisory is a leading advisory firm whose specialized professionals guide clients through an ever-changing business world, helping them win now and anticipate tomorrow. BTVK Advisory, and its affiliated entities, have operations in North America, South America, Europe, Asia, and Australia. BTVK Advisory’s ultimate parent entity, Baker Tilly US, LLP, is an independent member of Baker Tilly International, a worldwide network of independent accounting and business advisory firms in 141 territories, with 43,000 professionals and a combined worldwide revenue of $5.2 billion.

Baker Tilly is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, gender identity, sexual orientation, or any other legally protected basis, in accordance with applicable federal, state or local law.

To be added to all ET through Experienced requisitions Any unsolicited resumes submitted through our website or to Baker Tilly Advisory Group, LP, employee e-mail accounts are considered property of Baker Tilly Advisory Group, LP, and are not subject to payment of agency fees. In order to be an authorized recruitment agency ("search firm") for Baker Tilly Advisory Group, LP, there must be a formal written agreement in place and the agency must be invited, by Baker Tilly's Talent Attraction team, to submit candidates for review via our applicant tracking system.

Job Description:

Responsibilities :

• Experience designing distributed database architectures and building scalable model ecosystems to support enterprise AI initiatives.
• Lead the technical design of multi-agent workflows, utilizing a various toolkit (in Databricks) to solve complex, multi-layered AI problems.
• Work hands-on with models like OpenAI GPT, LLaMA, Claude, and others—fine-tuning or prompt-tuning as required.
• Own the entire AI project lifecycle, from research and prototyping to deployment and monitoring at scale following the enterprise standards.
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.
• Design and deploy high-availability model endpoints with health checks, error handling, retries, and fallback mechanisms.
• Implement evaluation frameworks and guardrails to eliminate logical errors, hallucinations, human in the loop and biases in Agent’s decision-making.
• Provides technical guidance and mentorship to junior team members. This includes sharing best practices, reviewing code and designs, and helping team members overcome technical challenges. Participate in technical discussions and provide thought leadership within the organization.
• Partner closely with Product Managers, Engineers, and Finance stakeholders to translate unique problems into concrete technical specification. Act as a self-sustaining technical leader who helps unblock system integration hurdles in partnership with Engineering teams.

Qualifications :

• Bachelor's degree is mandate, equivalent in Computer Science, Artificial Intelligence, Software Engineering, or a related field;
• Minimum 5 years experience in ML/AI engineering, or solution architecture, with significant technical-lead or architect experience.
• Deep, hands-on Databricks expertise: Unity Catalog, Delta Lake / Delta Live Tables, Workflows, MLflow, Mosaic AI, and vector search.
• Deep, hands-on understanding of how large language models and deep learning architectures work under the hood - from training and fine-tuning to inference.
• Proven delivery of GenAI and agentic systems (RAG, knowledge graphs, vector DBs, LLM evaluation) using frameworks like LangChain, LangGraph, LlamaIndex, DSPy, CrewAI.
• Production cloud experience on AWS and/or Azure: networking, identity, storage, and managed data/AI services.
• Hands-on experience balancing business priorities and technical delivery, bridging the gap between stakeholders and engineering teams.
• Hands-on MLOps / LLMOps: CI/CD for data and AI, model and prompt lifecycle, monitoring, and evaluation.
• Understanding of ontologies and knowledge graphs - designing schemas, modeling relationships, and using them to ground and enhance AI applications.
• Relevant cloud or Databricks certifications.