Senior AI Engineer
At a glance
Senior AI Engineering role at All Cares. Remote, United States · full-time · no salary stated · we estimate $162,273–$225,800 across the United States.
All Cares has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build LLM-based workflows that combine model reasoning, structured data and external tools for new product work
- Apply machine learning to forecast app usage, predict consumer behavior, estimate stock movements and segment users
- Find ways to add AI-driven predictions, automation and LLM-generated insights to existing models and datasets
- Test model ensembles and new LLM approaches, measuring quality, reliability, accuracy and cost
- Help shape internal AI infrastructure and take product ideas from early trials into production
What you bring
- At least five years in data science, machine learning, data engineering or applied AI
- You have delivered machine learning systems through the full production lifecycle
- Hands-on work with LLMs, plus experience using retrieval-augmented generation, tools or agent-based systems
- Strong Python skills and experience with APIs and cloud services, with AWS preferred
Who this fits
This senior role suits an engineer who can move between LLM product development, core modeling and AI infrastructure. You should be comfortable working through ambiguity and testing ideas quickly. It is a remote role in the United States.
From the employer
Senior AI Engineer
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
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