Description review

[ASP] Senior AI Engineer with Palantir

Software Mind · Poland · back to the listing

HR standards

46/100

poor

Title ↔ description

73/100

solid

Reads as

Machine Learning Engineer

99% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

How others title the same work

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Startups

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  • Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
  • Staff AI Engineer - Agent Architecture & Behavior Artisan

What the listing never says

  • 29 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

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.

Expectations – the experience you need

• 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.

Additional skills – the edge you have

• 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.

What we offer:

• Flexible and remote cooperation options

• International projects with leading global clients

• Travels related to international projects

• Non-corporate atmosphere

• Access* to language classes

• Access* to knowledge-sharing initiatives

• Access* to private healthcare and life insurance

• Access* to multisport card

*The availability and terms of individual benefits may vary depending on the chosen form of cooperation.

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.

Originally posted on Himalayas