Senior Systems Engineer, AI & Automation

Rapidly prototypes, implements, tests, deploys, and iterates production-ready AI-supported solutions using Cursor, GitHub Copilot, Microsoft Copilot, AI agents, LLM-based platforms, APIs, and automation tools. Practical experience using AI development and productivity tools such as Cursor, GitHub Copilot, Microsoft Copilot, AI agents, and LLM-based platforms to convert manual workflows into production-ready, AI-supported solutions.

Position Title: Senior Systems Engineer, AI & Automation
Location: Remote with travel to headquarters
Duration: 10 months with possible conversion

JOB SUMMARY:
We are seeking a hands-on AI Automation and Agent Implementation Consultant who will identify, design, and implement AI-enabled solutions that improve business processes and operational efficiency. The ideal candidate has practical experience using tools such as Cursor, GitHub Copilot, Microsoft Copilot, AI agents, and LLM-based platforms to transform manual workflows into production-ready, AI-supported solutions. This is an implementation-focused role for a builder who can rapidly prototype, implement, test, deploy, and operationalize AI solutions that deliver measurable business outcomes. It is not a strategy-only or advisory role.

Responsibilities:

• Designs and implements AI-enabled FinOps capabilities for cloud cost visibility, forecasting, anomaly detection, optimization recommendations, and executive reporting.
• Identifies high-value manual workflows and translates business requirements into implementable AI automation and agent use cases with defined outcomes and success measures.
• Rapidly prototypes, implements, tests, deploys, and iterates production-ready AI-supported solutions using Cursor, GitHub Copilot, Microsoft Copilot, AI agents, LLM-based platforms, APIs, and automation tools.
• Builds practical AI agents and workflow automations that integrate with enterprise systems, data sources, and operational processes while meeting security, privacy, architecture, and responsible AI requirements.
• Establishes evaluation, monitoring, observability, fallback, human-oversight, and support mechanisms to improve the reliability and maintainability of deployed AI solutions.
• Measures and communicates business outcomes from implemented solutions, including productivity, cycle time, quality, cost, adoption, and operational efficiency improvements.
• Establishes FinOps governance for AI/ML and GenAI workloads, including cost allocation, usage tracking, forecasting, budgeting, and optimization.
• Develop and maintain cost transparency for AI and machine learning workloads, including compute, storage, networking, model training, inference, and third-party AI platform usage.
• Create and manage reporting, dashboards, and KPIs to track AI-related spend, utilization, efficiency, and business value across teams and use cases.
• Partner with architecture, engineering, platform, and data science teams to identify opportunities to improve cost, performance, and utilization of AI infrastructure and services.
• Support the design and implementation of showback and chargeback models for AI-related services to improve accountability and decision-making.
• Analyzes cloud usage patterns, resource utilization, and spending to identify areas for improvement.
• Analyzes and implements cost optimization actions across cloud services.
• Implements and manages automated tools to identify cost trends and anomalies.
• Collaborates with finance and business teams to align cloud spending with budget constraints.
• Trains and mentors team members and peers, as appropriate.

Qualification:

• Bachelor s degree in an engineering or computer science discipline and/or equivalent experience/certification.
• 7 years of experience in information technology, including experience in cloud technologies (AWS, AliCloud, Azure), OS scripting, and automation using Python, Bash, or similar languages.
• Demonstrated hands-on experience identifying, designing, implementing, testing, and deploying AI-enabled automation or agent-based solutions that improve business processes and operational efficiency.
• Practical experience using AI development and productivity tools such as Cursor, GitHub Copilot, Microsoft Copilot, AI agents, and LLM-based platforms to convert manual workflows into production-ready, AI-supported solutions.
• Proven ability to move AI solutions beyond experimentation into production, with measurable outcomes such as efficiency gains, cycle-time reduction, quality improvement, risk reduction, or cost savings.
• Experience rapidly prototyping and iterating AI solutions, integrating them with enterprise workflows, APIs, data sources, and automation platforms, and supporting production deployment and operational readiness.

Preferred:

• Excellent problem-solving skills, with the ability to work independently and lead outcomes across cross-functional teams.
• Excellent verbal and written communication skills for executives, business stakeholders, and IT teams.
• Experience with services such as Amazon Bedrock, SageMaker, Azure OpenAI, Azure AI Foundry, Google Vertex AI, OpenAI APIs, Anthropic, Databricks, Snowflake AI, or similar platforms.
• Experience with AI agent frameworks, retrieval-augmented generation, prompt and context engineering, model evaluation, observability, responsible AI controls, secure deployment patterns, and human-in-the-loop workflows.
• Experience defining and tracking implementation success measures, documenting reusable solution patterns, and transitioning AI-enabled capabilities to operations and support teams.
• Experience supporting generative AI or large language model workloads, including token-based pricing models and inference cost optimization.
• Experience in developing and implementing FinOps/Cloud Cost Optimization strategies.

EEO:
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.