Mid-Level AI Engineer / AI Developer
We are seeking a Mid-Level AI Engineer to design, develop, deploy, and support AI-powered applications and services that deliver business value at scale. This role works closely with software engineers, product managers, architects, data teams, and business stakeholders to build enterprise-grade AI solutions using modern machine learning techniques, generative AI platforms, agent frameworks, and cloud-native software engineering practices.
Professional Experience
3–6 years of software engineering or application development experience.
2+ years of hands-on experience delivering AI, machine learning, or Generative AI solutions.
Key Responsibilities
AI Application Development
Design, develop, test, deploy, and maintain AI-enabled applications and services.
Build and integrate Generative AI solutions using Large Language Models (LLMs) and foundation models.
Develop AI-powered copilots, assistants, conversational experiences, and enterprise automation solutions.
Engineer scalable AI workflows that leverage prompt orchestration, tool usage, and agent-based interactions.
Translate business requirements into secure, reliable, and maintainable technical solutions.
Generative AI & Agent Engineering
Develop AI agents, tools, workflows, and orchestration frameworks.
Design and implement Retrieval-Augmented Generation (RAG), semantic search, and enterprise knowledge retrieval solutions.
Build and maintain MCP (Model Context Protocol) integrations, tool-calling frameworks, and multi-agent systems.
Create and optimize prompts, system instructions, and evaluation processes to improve AI performance and reliability.
Evaluate model behavior and implement strategies for improving response quality, grounding, and accuracy.
Software Engineering & Platform Development
Build APIs, microservices, and backend services that support AI workloads.
Develop reusable components and services that enable scalable AI capabilities across the organization.
Apply software engineering best practices including code reviews, testing, documentation, and version control.
Participate in architectural design and technical decision-making for AI solutions and platforms.
Ensure AI services meet performance, scalability, security, and availability requirements.
AI Operations & Optimization
Evaluate, benchmark, and optimize AI models for quality, latency, reliability, and cost efficiency.
Implement automated testing, monitoring, logging, and observability for AI applications.
Support AI systems in production environments and participate in troubleshooting, incident response, and root cause analysis.
Monitor application performance and implement continuous improvements based on usage and operational insights.
Establish evaluation frameworks and performance benchmarks for AI systems.
Governance, Security & Compliance
Implement responsible AI practices and enterprise governance requirements.
Ensure AI solutions comply with security, privacy, and regulatory requirements.
Apply guardrails, content controls, identity management, and access controls where appropriate.
Collaborate with security, compliance, and architecture teams to mitigate risks associated with AI deployments.
Required Qualifications
Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, or a related technical field.
3–6 years of software development experience.
Minimum 2 years of experience developing AI, machine learning, or Generative AI solutions.
Strong programming skills in one or more of the following:
Python
Java
C#
JavaScript / TypeScript
Experience designing and developing RESTful APIs and distributed services.
Experience working with cloud platforms including:
Microsoft Azure
Amazon Web Services (AWS)
Google Cloud Platform (GCP)
Solid understanding of software engineering fundamentals, including:
Object-oriented design
Design patterns
Automated testing
CI/CD pipelines
Application security
Monitoring and observability
Experience working within Agile software development environments.
Strong problem-solving, analytical, and communication skills.
Preferred Qualifications
Experience working with industry-leading AI platforms and models, including:
OpenAI
Azure OpenAI
Anthropic Claude
Google Gemini
Experience developing:
AI agents
Agent orchestration platforms
MCP-based integrations
Tool-calling frameworks
Multi-agent workflows
Experience implementing RAG architectures and enterprise knowledge search solutions.
Familiarity with vector databases, embeddings, semantic search, and knowledge retrieval systems.
Experience with prompt engineering, prompt evaluation, and AI benchmarking frameworks.
Experience with containerization and orchestration technologies, including:
Docker
Kubernetes
Cloud Run
Experience deploying and operating cloud-native applications.
Knowledge of Responsible AI, AI governance, and enterprise AI risk management practices.