Description review
AI Engineer
Nimble Gravity · United States · back to the listing
HR standards
56/100
needs work
Title ↔ description
83/100
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
Large employers
- Applied AI Engineer Automattic
- Machine Learning Engineer, CX Intelligence Coinbase
- AI Engineer - FDE (Forward Deployed Engineer) Databricks
- AI Engineer - FDE (Forward Deployed Engineer) - U.S. Federal Sector Databricks
- Senior AI Engineer – Notebooks Datadog
Startups
- Attendi | Medior Machine Learning Engineer | Amsterdam, Netherlands | ONSITE (hybrid) | €6,000 - €7,000 per month | Full-time (80–100%, ~4–5 days/week) | Visa sponsorship + 30% ruling possible Attendi
- Member of Technical Staff (applied) Anthrogen
- Aptura AI | Full-Time | MTS (Applied AI), MTS (SWE / Product) | London | ONSITE / HYBRID Aptura AI
- Arcforma AI (arcforma.ai) | AI Engineer (Marketing / Construction / Arcforma AI (arcforma.ai)
- Staff AI Engineer - Agent Architecture & Behavior Artisan
What the listing never says
- 18 bullet points. Long requirement lists deter qualified candidates, who read them as hard gates. Scope clarity
- No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
- No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity
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.
Sr AI Engineer – Generative AI & Agentic Systems
We’re looking for an exceptional SrAI Engineer to join our growing Data & AI practice and help build the next generation of AI-powered solutions.
This role is ideal for someone who loves working at the edge of what’s possible with LLMs, RAG, agents, semantic search, multimodal AI, and intelligent automation — and who wants to turn cutting-edge ideas into real, production-ready systems for clients across industries.
This position is open to candidates based in LATAM or the United States.
What You’ll Do
• Design, build, and deploy advanced AI solutions using LLMs, RAG, embeddings, vector databases, semantic search, and agentic architectures.
• Develop intelligent systems that can process documents, retrieve knowledge, generate content, automate workflows, and transform unstructured data into actionable insights.
• Work with modern GenAI and AI engineering tools such as LangChain, LangGraph, Hugging Face, PyTorch, MCP, multi-agent frameworks, and cloud-native AI services.
• Build scalable, reliable AI applications across Azure, AWS, Databricks, or similar cloud/data platforms.
• Experiment with and evaluate foundation models, prompts, retrieval strategies, orchestration patterns, and performance optimization techniques.
• Collaborate closely with engineering, product, data, and business teams to define the right technical approach and deliver high-impact AI solutions.
• Stay plugged into the fast-moving GenAI ecosystem and bring new ideas, tools, and prototypes into real-world applications.
What You Bring
• Strong experience in AI, machine learning, data science, or AI engineering, with hands-on exposure to production-scale solutions.
• Deep interest and practical experience with Generative AI, including LLMs, RAG, vector search, embeddings, agents, and AI workflow orchestration.
• Strong Python skills and experience with modern ML/AI frameworks and libraries.
• Experience building on cloud or data platforms such as Azure, AWS, GCP, Databricks, or similar.
• A solid foundation in data science, experimentation, statistical thinking, or applied machine learning.
• Ability to work with structured and unstructured data, including text, documents, images, emails, spreadsheets, or other complex data formats.
• A builder mindset: curious, hands-on, adaptable, and excited to work with emerging technologies.
• Strong communication skills and the ability to partner with technical and non-technical stakeholders.
Nice to Have
• Advanced degree in Computer Science, Data Science, AI, Machine Learning, or a related technical field.
• Experience with MCP, multi-agent systems, fine-tuning, LLM evaluation frameworks, multimodal AI, or production ML observability.
• Prior consulting, client-facing, or cross-functional delivery experience.
About Nimble Gravity
Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization.
Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants.
Originally posted on Himalayas
We’re looking for an exceptional SrAI Engineer to join our growing Data & AI practice and help build the next generation of AI-powered solutions.
This role is ideal for someone who loves working at the edge of what’s possible with LLMs, RAG, agents, semantic search, multimodal AI, and intelligent automation — and who wants to turn cutting-edge ideas into real, production-ready systems for clients across industries.
This position is open to candidates based in LATAM or the United States.
What You’ll Do
• Design, build, and deploy advanced AI solutions using LLMs, RAG, embeddings, vector databases, semantic search, and agentic architectures.
• Develop intelligent systems that can process documents, retrieve knowledge, generate content, automate workflows, and transform unstructured data into actionable insights.
• Work with modern GenAI and AI engineering tools such as LangChain, LangGraph, Hugging Face, PyTorch, MCP, multi-agent frameworks, and cloud-native AI services.
• Build scalable, reliable AI applications across Azure, AWS, Databricks, or similar cloud/data platforms.
• Experiment with and evaluate foundation models, prompts, retrieval strategies, orchestration patterns, and performance optimization techniques.
• Collaborate closely with engineering, product, data, and business teams to define the right technical approach and deliver high-impact AI solutions.
• Stay plugged into the fast-moving GenAI ecosystem and bring new ideas, tools, and prototypes into real-world applications.
What You Bring
• Strong experience in AI, machine learning, data science, or AI engineering, with hands-on exposure to production-scale solutions.
• Deep interest and practical experience with Generative AI, including LLMs, RAG, vector search, embeddings, agents, and AI workflow orchestration.
• Strong Python skills and experience with modern ML/AI frameworks and libraries.
• Experience building on cloud or data platforms such as Azure, AWS, GCP, Databricks, or similar.
• A solid foundation in data science, experimentation, statistical thinking, or applied machine learning.
• Ability to work with structured and unstructured data, including text, documents, images, emails, spreadsheets, or other complex data formats.
• A builder mindset: curious, hands-on, adaptable, and excited to work with emerging technologies.
• Strong communication skills and the ability to partner with technical and non-technical stakeholders.
Nice to Have
• Advanced degree in Computer Science, Data Science, AI, Machine Learning, or a related technical field.
• Experience with MCP, multi-agent systems, fine-tuning, LLM evaluation frameworks, multimodal AI, or production ML observability.
• Prior consulting, client-facing, or cross-functional delivery experience.
About Nimble Gravity
Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization.
Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants.
Originally posted on Himalayas