Agentic AI Engineer

Key ResponsibilitiesAI System Design & Development (25%)

• Lead the design, development, and implementation of AI-driven agentic systems.
• Develop software solutions enabling communication between AI agents, external APIs, and enterprise services.
• Write high-performance, testable, and maintainable code using Python and other relevant languages.
• Build and deploy large-scale models leveraging open-source and commercial LLMs, ML/DL/RL frameworks, and agentic tools.
• Establish monitoring, logging, and debugging protocols for production-level agentic systems.

Optimization & Automation (25%)

• Identify and optimize workflow inefficiencies through AI-powered automation.
• Evaluate results for accuracy, performance, and scalability across multiple environments.
• Implement secure, ethical, and transparent AI workflows adhering to organizational and compliance guidelines.
• Utilize data-driven methods to enhance agent performance and reduce manual overhead.

Project Leadership & Collaboration (25%)

• Act as technical lead on projects, collaborating with Product Owners, Data Scientists, and Solution Architects.
• Participate in architectural discussions, roadmap planning, and technical reviews.
• Provide estimates, risk assessments, and strategic recommendations on AI initiatives.
• Mentor junior engineers and foster knowledge sharing across teams.

Integration & Deployment (25%)

• Design and maintain CI/CD pipelines for AI model deployment using Kubernetes, Docker, and Jenkins.
• Develop RESTful APIs and integrate AI systems with existing cloud infrastructure (preferably AWS).
• Ensure compliance with DevSecOps practices and enterprise-grade security standards.
• Support continuous improvement and adoption of emerging technologies to maintain a competitive edge.

Required Skills & Experience

• 3+ years of experience building production-level AI or ML systems, including LLMs, intelligent agents, or automation frameworks.
• Strong proficiency in Python, with hands-on experience using libraries such as Pandas, NumPy, PyTorch, or TensorFlow.
• Expertise in NLP, Machine Learning, Deep Learning, and Reinforcement Learning.
• Proven experience developing and integrating AI agents using frameworks such as LangChain, LangGraph, or similar.
• Experience connecting agents to APIs, databases, and cloud services.
• Strong understanding of SDLC, DevSecOps, and agile development methodologies.
• Hands-on experience with Cloud Service Providers (AWS preferred) and containerization technologies (Docker, Kubernetes).
• Experience with REST API development (Java, Spring Boot preferred).
• Familiarity with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
• Excellent problem-solving skills and the ability to debug, optimize, and scale production AI systems.

Preferred Qualifications

• Bachelor's Degree in Computer Science, Information Technology, or related field.

(In lieu of a degree, an additional 4 years of relevant work experience is acceptable.)

• 8+ years of professional experience in software design, development, and testing.
• Proficiency in modern programming languages such as Python, JavaScript, or C.
• Strong understanding of cloud-native architectures, databases (SQL, PostgreSQL, MongoDB), and CI/CD best practices.
• Proven experience deploying global-scale applications.
• Demonstrated ability to mentor engineers, lead cross-functional technical discussions, and deliver high-impact systems.
• Knowledge of TDD/BDD methodologies and automated testing frameworks.
• Excellent verbal and written communication skills with the ability to present technical solutions to non-technical stakeholders.

Job Type: Contract

Pay: $ $70.00 per hour

Expected hours: 40 per week

Application Question(s):

• How many years of hands-on experience do you have building and deploying production-level AI or ML systems (including LLMs or AI agents)?
• Which programming languages and frameworks are you most comfortable with specifically Python, PyTorch, TensorFlow, LangChain, or LangGraph?
• Do you have experience working with cloud platforms such as AWS (or others like GCP/Azure), and have you used Docker or Kubernetes for deployment?
• Have you previously integrated AI agents or models with external APIs, databases, or enterprise systems to automate workflows?
• What tools have you used for continuous integration and deployment (e.g., Jenkins, GitHub Actions, GitLab CI), and how comfortable are you with DevSecOps practices?
• How do you ensure AI systems you build follow ethical, transparent, and fair-use guidelines and how do you typically collaborate with data scientists or cross-functional teams?
• Current visa status
• Desired Salary

Ability to Commute:

• Remote (Required)

Work Location: Remote