EarnIn is making AI-native engineering a core capability — not an initiative, but how we design, build, and ship. We're not hiring a software engineer who dabbles in AI. We're hiring an AI builder who also writes great software — someone who looks at every step of how we design, build, test, and ship, and asks: why isn't an agent doing this? This is not a side project. The agents and harnesses you build here will run in production, making real decisions for real people — people who depend on EarnIn to access their pay when it matters most.
Compensation
The Mountain View base salary range for this full-time position is $228,000 - $279,000, plus equity and benefits.
Responsibilities
Design how agents think (prompts, reasoning chains, tool calls, and full architecture)
Build the layer every squad at EarnIn builds on (MCP servers, agent scaffolding, context harnesses, Skills Marketplace)
Challenge and replace manual friction in the product development lifecycle with agentic workflows
Own the evaluation infrastructure (pipelines, benchmarks, quality gates)
Take working AI pilots and turn them into production-ready, reusable libraries and templates
Senior Platform Engineer focused on designing, integrating, and operationalizing AI agents and agentic workflows within secure enterprise environments.
Locations (2)
Springfield, Virginia, United States
United States
Compensation
Full compensation packages are based on candidate experience. Compensation ranges are established using national benchmarking data and apply across all geographic locations within the United States. Remote - USA $148,750—$201,250 USD
Responsibilities
Design, build, and integrate AI agents and multi-agent workflows using modern LLM and agentic technologies.
Develop agent capabilities that interact with enterprise applications, APIs, data sources, developer tools, and mission systems.
Integrate models, agents, tools, and enterprise data into secure workflows that can be deployed in controlled and classified environments.
Work with LLMs, RAG, embeddings, vector databases, tool/function calling, structured outputs, MCP, and related technologies.
Develop mechanisms for agents to securely discover, access, reason over, and act upon approved enterprise data and services.
V
Applied AI Engineer – GenAI Platform (Credit Complex)
Design, build, and maintain data lineage and Gen AI/LLM-powered systems for large, multi-language codebases, owning backend services, deployment pipelines, and user-facing interfaces.
Compensation
$94,300.00 - $141,500.00
Responsibilities
Design and build engines that parse multiple programming and query languages to extract accurate, column-level data lineage.
Build Gen AI/LLM-powered retrieval and assistant capabilities on top of lineage and metadata.
Develop backend services and interfaces that expose them, from data processing through to user-facing views.
Own the delivery pipeline—build, test, deployment, and production support across environments.
Translate ambiguous requirements into clean, efficient, well-structured designs.
Requirements
Bachelor’s degree/University degree or equivalent experience
As a Senior AI Engineer on the Microsoft Office AI team, you will bring AI-native work experiences across Copilot in Office and the Copilot SuperApp, turning insights into production-grade domain agents.
Locations (3)
Redmond, Washington, United States
San Francisco, California, United States
New York, New York, United States
Compensation
Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Responsibilities
Architect, prototype, and lead the iteration on AI agent experiences that reimagine domain-specific workflows across Copilot in Office and Copilot Cowork
Drive the delivery of features by operating at the intersection of SWE, applied science, product, and domain expertise
Applications Development Sr Programmer Analyst - Assistant Vice President
Build autonomous and semi‑autonomous AI agents and multi‑agent systems for enterprise applications.
Compensation
The range listed is just one component of BMC's employee compensation package. Other rewards may include a variable plan and country specific benefits. At BMC, it is not typical for an individual to be hired at /near the top of the range. A reasonable estimate of the current range is zł 251,025 - zł 418,375
Responsibilities
Design, develop, and maintain enterprise‑grade agentic AI applications using modern LLMs and AI frameworks.
Build autonomous and semi‑autonomous AI agents capable of planning, reasoning, decision‑making, and task execution.
Develop multi‑agent systems and orchestrate interactions between agents, tools, APIs, and enterprise applications.
Integrate AI agents with internal and external services through APIs, databases, messaging systems, and workflow engines.
Build and deploy RAG solutions using vector databases and enterprise knowledge sources.
Requirements
Bachelor's or Master's in Computer Science, AI, ML, or related field (or equivalent experience)
Nice to have: frontier/foundation models beyond API usage
Nice to have: open‑weight models and local inference (vLLM, Ollama, Hugging Face)
Nice to have: data exploration techniques and tools
Build autonomous and semi-autonomous AI agents, develop multi-agent systems, integrate with enterprise applications, and lead AI architecture.
Compensation
The range listed is just one component of BMC's employee compensation package. Other rewards may include a variable plan and country specific benefits. At BMC, it is not typical for an individual to be hired at /near the top of the range. A reasonable estimate of the current range is zł 251,025 - zł 418,375
Responsibilities
Design, develop, and maintain enterprise-grade agentic AI applications using modern LLMs and AI frameworks.
Build autonomous and semi-autonomous AI agents capable of planning, reasoning, decision-making, and task execution.
Develop multi-agent systems and orchestrate interactions between agents, tools, APIs, and enterprise applications.
Integrate AI agents with internal and external services through APIs, databases, messaging systems, and workflow engines.
Build and deploy RAG solutions using vector databases and enterprise knowledge sources.
Requirements
Bachelor's or Master's in Computer Science, AI, ML, or related field (or equivalent experience).
Nice to have: Frontier/foundation models beyond API usage
Nice to have: Open-weight models and local inference (vLLM, Ollama, Hugging Face)
Nice to have: Data exploration techniques and tools
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