Senior AI Engineer

AllCares; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Apptopia is seeking a Senior AI Engineer to join our data-driven, high-growth team and lead our push into LLMs, agentic systems, and AI-powered product innovation.

You will design and build intelligent systems that fuse LLM reasoning with structured data and external tools, shaping how we use AI across our products and company.

Qualifications

• 5+ years in data science, ML, data engineering, or applied AI.
• Experience building production ML systems end-to-end.
• Hands-on experience with LLMs (OpenAI, Anthropic, Bedrock, etc.).
• Experience with RAG, tool use, or agentic systems.
• Strong Python + APIs and cloud experience (AWS preferred).

Responsibilities

• Incorporate LLM powered systems into data products to advance existing products and AI strategy.
• Lead efforts to bring new finance-focused products to market with LLMs.
• Design and implement agentic workflows combining LLMs, data, and tools.
• Experiment with multi-step reasoning, RAG, tool orchestration, and new paradigms.
• Develop ML algorithms for use cases like usage forecasting and user segmentation.
• Contribute to evolving core modeling and AI platform infrastructure.

Skills

Python & APIs

LLM systems

Data science / ML engineering

Cloud (AWS) experience

Experimentation & ambiguity tolerance

Tools

Databricks

AWS tooling

Job description

Apptopia is seeking a Senior AI Engineer to join our dynamic, data-driven team at a high-growth startup backed by powerhouse investors like Mark Cuban and ABS Capital. We specialize in providing actionable competitive intelligence to investment firms and financial institutions by estimating worldwide downloads, revenues, and active users for every mobile app. We also provide a unique, highly valued product with app user behavior insights. Our actionable app-store data and intuitive business intelligence tool help companies like Google, Facebook, and top hedge funds make smarter decisions.

Apptopia is hiring a Senior AI Engineer to lead our push into LLMs, agentic systems, and AI-driven product innovation.

You’ll design and build intelligent systems that combine LLM reasoning, structured data, and tool orchestration—shaping how we use AI across our product and company.

Responsibilities

• You will be a Senior AI Engineer on the Product team where you will work on incorporating LLM powered systems into new data products, advance our existing products and help shape Apptopia's long term AI strategy.
• You will spearhead efforts to incorporate LLM powered systems as we bring new finance focused products to market
• Design and implement agentic workflows that combine LLM reasoning, structured data, and external tools to accelerate new product delivery
• Experiment with multi-step reasoning systems, RAG, tool orchestration, and emerging paradigms to improve analyst workflows
• Design, develop, and implement machine learning algorithms to advance a broad set of use cases including app usage trend forecasting, consumer behavior prediction,, stock price movement estimation, user segmentation
• You will take part, and in many cases lead the thought process for improving core modeling efforts:
• Identify opportunities to extend existing modeling work into AI-native systems that integrate predictions, reasoning, and automation
• Identify opportunities to augment core datasets with LLM-derived features, classifications, and insights
• Research, identify, and test ensemble methodologies to continuously improve accuracy and coverage in our models used for core app usage estimates
• You will be a key thought leader in development of our AI platform and infrastructure: Contribute to the design of internal AI platforms that enable teams to leverage LLMs at scale
• Lead rapid experimentation cycles to evaluate new LLM capabilities, architectures, and vendors
• Define frameworks for evaluating LLM quality, reliability, and cost-performance tradeoffs
• Partner with product and engineering to take ideas from 0 → production
• Help define best practices for prompting, memory, tool use, and system architecture

Required Qualifications

• 5+ years in data science, ML, data engineering, or applied AI
• Experience building production ML systems end-to-end
• Hands‑on experience with LLMs (OpenAI, Anthropic, Bedrock, etc.)
• Experience with RAG, tool use, or agentic systems
• Strong Python + experience with APIs and cloud (AWS preferred)
• Databricks tooling experience preferred
• Comfortable with ambiguity and fast experimentation cycles
• Familiarity with click stream, app usage, and/or observational panel data preferred