Managing Consultant, Palantir Data & AI EngineerDepartment: Data Analytics
Employment Type: Full Time
Location: Atlanta
The RoleWe are looking for a technically skilled and motivated Managing Consultant with hands-on Palantir experience to join our growing Data & Analytics team. In this role, you will work directly with clients to design, build, and deploy solutions using Palantir Foundry and, where applicable, Palantir AIP. You will translate complex business problems into production-ready data and AI solutions, lead project workstreams, and help clients turn their data into measurable business outcomes.
What You'll Do- Design, build, and deploy scalable data and AI solutions using Palantir Foundry, with emphasis on Foundry data pipelines, data modeling, and operational workflows.
- Develop and prototype GenAI- and LLM-powered solutions using Palantir AIP and related enterprise AI capabilities.
- Embed with client teams to identify high-value use cases, translate business requirements into technical solutions, and lead working sessions with senior stakeholders.
- Build production-quality data and AI applications using strong engineering practices including testing, CI/CD, version control, logging, documentation, and performance optimization.
- Develop agentic AI workflows, tool-use patterns, and human-in-the-loop controls while balancing quality, safety, latency, cost, and model risk.
- Integrate Palantir solutions with enterprise systems, cloud platforms, APIs, microservices, and data sources to create reliable end-to-end solutions.
- Lead project workstreams and mentor team members while creating reusable Palantir assets, implementation patterns, documentation, and reference solutions.
Who You'll Work With- Client executives, business leaders, product owners, architects, engineers, and data teams focused on modernizing data and AI capabilities.
- Palantir-focused delivery teams working across Foundry, AIP, data engineering, AI, and application development.
- Cross-functional client teams where you will operate directly in the business to understand problems and rapidly deliver working solutions.
- Experienced Thought Logic consultants and technical leaders who provide architectural guidance, delivery support, and mentorship.
- Organizations looking to operationalize Palantir Foundry and AI capabilities to improve mission-critical business processes and decision-making.
- Technical and non-technical stakeholders who need complex data and AI concepts translated into practical, business-focused solutions.
- A collaborative consulting environment that values curiosity, ownership, hands-on problem solving, and measurable client outcomes.
What You'll Bring- Professional experience in data engineering, software engineering, analytics engineering, data science, or a related technical discipline.
- Hands-on Palantir experience, including meaningful implementation experience with Palantir Foundry and/or Palantir AIP.
- Experience building and deploying production GenAI/LLM-powered solutions and translating business problems into practical AI use cases.
- Strong data engineering fundamentals including SQL, Python or another scripting language, ETL/ELT, data modeling, data integration, and data quality.
- Experience with cloud environments such as AWS, Azure, and/or Google Cloud and modern data technologies such as Spark, Airflow/dbt, streaming, or similar platforms.
- Ability to lead client-facing workstreams, communicate effectively with senior stakeholders, and operate successfully in ambiguous, fast-paced consulting environments.
- Bachelor's degree in Computer Science, Data Engineering, Data Science, Information Systems, Engineering, or a related field; ability to legally work for any employer in the U.S. without sponsorship.
Bonus Points if You Have- Palantir certifications, advanced Foundry experience, or experience with Palantir AIP, Maven, or other Palantir products.
- Experience developing ontology-driven applications, operational workflows, or applications directly within the Palantir Foundry ecosystem.
- Experience with MLOps/LLMOps, including model evaluation, monitoring, prompt management, experimentation, and model risk considerations.
- Experience integrating LLM solutions with enterprise systems through APIs, microservices, or event-driven architectures.
- Experience with Databricks, Snowflake, Azure Data Factory, AWS Glue, Redshift, Kafka, Power BI, Tableau, or comparable modern data technologies.
- Experience with agentic AI frameworks, retrieval-augmented generation, tool use, or human-in-the-loop AI patterns.
- Previous consulting firm experience and a track record of delivering technology solutions directly alongside client technical teams.
