[ASP] Senior AI Engineer with Palantir

Software Mind

1d•Remote

About The Position

Software Mind develops solutions that make an impact for companies around the globe. Tech giants & unicorns, transformative projects, emerging technologies and limitless opportunities – these are a few words that describe an average day for us. Building cross-functional engineering teams that take ownership and crave more means we’re always on the lookout for talented people who bring passion and creativity to every project. Our culture embraces openness, acts with respect, shows grit & guts and combines employment with enjoyment. Project – the aim you’ll have You will join a 15-month AI transformation engagement for an international management consulting client, delivering production-ready Agentic AI solutions across diverse business use cases. Working in one of two cross-functional pods of Senior Data and AI Engineers, you will take solutions from ideation and experimentation through deployment. The project offers hands-on work with Palantir Foundry and AIP, modern LLMs, Azure and Databricks in a fast-paced environment. Role – how you’ll contribute Design, build, test and productionize Agentic AI solutions across the end-to-end use case lifecycle. Develop modular AI agents, tools and reusable capabilities supporting multiple business use cases. Engineer data pipelines and data products for structured and unstructured data using Palantir Foundry. Design and maintain Foundry ontologies, including Object Types, Link Types, Action Types, Interfaces and Property Sets. Build and deploy LLM-powered workflows using Palantir AIP Logic, AIP Automate and AIP Assist. Integrate and evaluate models from OpenAI, Anthropic and other LLM providers, considering quality, security and cost. Implement automated testing, observability, guardrails and secure CI/CD pipelines supporting production deployments. Collaborate with client stakeholders and pod members, sharing Palantir expertise and upskilling other engineers.

Requirements

Strong commercial experience designing, building and deploying Agentic AI and multi-agent solutions in production environments.
Hands-on experience with Palantir Foundry and Palantir AIP, covering data engineering, ontology development and AI/LLM workflows.
Strong Python skills and practical experience with agent frameworks such as LangGraph, LangChain, LlamaIndex or similar.
Experience building data pipelines and semantic or context layers using structured and unstructured data.
Hands-on experience with leading LLM providers, RAG architectures, vector databases and model integration.
Experience with Git-based development, automated testing, CI/CD pipelines and DevSecOps practices.
Understanding of LLM evaluation, AI guardrails, observability and responsible AI principles.
Strong English communication skills and the ability to collaborate with clients, cross-functional teams and other engineers.

Nice To Haves

Experience with advanced Palantir capabilities such as CBAC attribute sets, Data Lineage, Ontology Linter and Foundry Marketplace.
Hands-on knowledge of Azure AI Foundry, Databricks and Databricks Genie.
Experience designing semantic layers, ontologies or context spines across Azure, AWS or GCP environments.
Knowledge of LLM model selection, performance optimization and cost management.
Previous experience in consulting, rapid prototyping or upskilling engineering teams.

Responsibilities

Design, build, test and productionize Agentic AI solutions across the end-to-end use case lifecycle.
Develop modular AI agents, tools and reusable capabilities supporting multiple business use cases.
Engineer data pipelines and data products for structured and unstructured data using Palantir Foundry.
Design and maintain Foundry ontologies, including Object Types, Link Types, Action Types, Interfaces and Property Sets.
Build and deploy LLM-powered workflows using Palantir AIP Logic, AIP Automate and AIP Assist.
Integrate and evaluate models from OpenAI, Anthropic and other LLM providers, considering quality, security and cost.
Implement automated testing, observability, guardrails and secure CI/CD pipelines supporting production deployments.
Collaborate with client stakeholders and pod members, sharing Palantir expertise and upskilling other engineers.