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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** AKIVA AI - **Location:** United States (Remote available) - **Experience:** Starter - **Salary:** $125,000.0 - $225,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Audit Trail, Automation of Tests, Microsoft Azure, Bash Shell, Cloud Computing, Information Engineering, Data Governance, Data Security, DevOps, File Transfer, Monitoring of Systems, Python (Programming Language), Machine Learning, Microsoft SQL Server, Windows PowerShell, Scrum Methodology, Power BI, Software Engineering, SQL Databases, Systems Integration, Tableau (Software), Data Logging, Google Cloud, File Transfer Protocol (FTP), Enterprise Software Applications, Large Language Models, Multi-Agent Systems, Machine Learning Operations, Restful APIs, Data Pipelines - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ec0709ad1824c194 ## About the Role * Experience in software engineering, AI/ML, data engineering, or enterprise systems, commensurate with level. * Proficiency in Python and SQL (SQL Server preferred). * Experience working with REST APIs and integrated enterprise systems. * Familiarity with cloud-based environments (Azure, AWS, or equivalent). * Understanding of AI/ML concepts, including model deployment and lifecycle management. * Exposure to or experience with agent-based systems, orchestration, or workflow automation. * Experience supporting or contributing to production systems. Preferred Qualifications * Experience with multi-agent systems, agent orchestration frameworks, or agentic platforms. Familiarity with agent frameworks (e.g., LangChain, AutoGen, CrewAI, or custom frameworks). * Experience with monitoring and observability tools Familiarity with vector databases, semantic retrieval, and AI-enabled dashboards. * Experience with cognitive architectures, neural network-based models, or hybrid symbolic/LLM systems used in production environments. Tools, Technologies & Frameworks * Languages: Python, SQL, PowerShell/Bash * Databases: SQL Server * AI & Agentic Systems: LLM-based agents, multi-agent orchestration frameworks, vector databases * Integration: REST APIs, FTP/SFTP * Cloud: Azure, AWS, GCP * DevOps & Ops: CI/CD pipelines, infrastructure as code, monitoring and logging tools * Visualization: Power BI, Tableau, or custom dashboards Methodologies & Practices Agile / Scrum Secure Software Development Lifecycle (SDLC) * MLOps and AgentOps best practices Data governance, auditability, and compliance controls Responsible and explainable AI practices ## Description AKIVA is seeking AI Engineers across multiple experience levels (Junior, Mid-Level, Senior, and Subject Matter Expert) to design, build, integrate, and operate production-grade AI and agentic systems supporting enterprise and government programs. This role supports regulated, compliance-driven environments, including data-intensive platforms, dashboards, automation workflows, and multi-system integrations critical to program oversight, reporting, and operational efficiency. AI Engineers at AKIVA work across the full lifecycle-from strategy and architecture through deployment and production support-delivering secure, scalable, and auditable AI solutions, including multi-agent systems, orchestration frameworks, and agent-based task coordination for complex workflows. Key Responsibilities (All Levels) * Design, develop, and maintain AI-enabled and agentic systems for enterprise and government use cases. * Build and operate multi-agent workflows, including agent coordination, orchestration, and tool invocation. * Develop secure data pipelines for ingestion, transformation, and validation. * Integrate AI solutions with enterprise platforms and systems using REST APIs, SQL Server, and secure file transfer. * Support production dashboards, automation scripts, and scheduled/overnight processes. Monitor, troubleshoot, and optimize AI systems, data pipelines, and integrations. * Contribute to or lead DevOps, MLOps, and AgentOps practices, depending on level. * Ensure solutions comply with data security, governance, and audit requirements. 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