Applied AI Engineer
Remote · USFull-timePosted 4 days agoStill listed today
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At a glance
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Job overview
Bjak’s ActAI team is building an agent-first mobile communication app intended to bring AI into everyday communication, coordination, and collaboration with minimal prompting. The Applied AI Engineer builds and deploys AI features, agent workflows, backend integrations, and evaluations, then improves their reliability, latency, and cost. The role works with engineering and product teams to develop, test, and release AI features.
Skills & qualifications
Skills
Qualifications
Full job description
About ActAI There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting. Our first application is an agent-first mobile communication app. We believe building applications that users use daily for communication, coordination and collaboration needs will help integrate AI into their lives. The net effect is to eliminate misinformation, achieve low coordination costs, enable high quality tasks and collaboration at scale with minimal or little prompting.
Role
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Build and deploy AI features using LLMs, tool calling and agent workflows
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Develop prompting, context management, memory and orchestration systems for multi-step tasks
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Build backend APIs and integrations that connect AI models with applications and external tools
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Develop evaluations to measure task completion, response quality and system reliability
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Debug model outputs, tool failures and agent behaviour using production logs and evaluation results
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Improve response latency, inference costs and reliability of AI applications
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Work with engineering and product teams to develop, test and release AI features
Requirements
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3+ years of software engineering or machine learning engineering experience, including building AI applications
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Strong Python programming skills and experience developing production backend systems
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Hands-on experience with LLM APIs, prompting, tool calling and agent workflows
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Understanding of LLM capabilities, limitations, inference and context management
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Experience evaluating AI outputs, debugging failures and improving model-driven workflows
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Knowledge of APIs, databases, asynchronous processing and distributed systems
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Experience deploying, monitoring and maintaining production applications
Nice to Have
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Experience with RAG, embeddings, vector databases and retrieval systems
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Experience with open-source models such as Llama or Qwen and inference frameworks such as vLLM
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Experience with model fine-tuning using PyTorch or JAX
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Experience building AI-powered consumer applications, particularly messaging or productivity products
How this job compares
Set against the 6,303 open Machine Learning Engineer jobs on Olive Jobs, counted November 10, 2026.
- Pay
- This postingNot listed
- US median$150–246K/yr5,155 salary ranges
- US median$35–70/hr113 hourly ranges
- Openings
- Olive Jobs lists 6,303 open Machine Learning Engineer jobs across the US. 8% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 3 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (5,040 postings).
- Education
- 2,037 of the 6,303 open Machine Learning Engineer jobs (32%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 10, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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