Senior Engineer

Key Responsibilities

AI Agents & Intelligent Automation

• Build and operate Python-based automation frameworks for security and engineering workflows.
• Develop LLM-powered agentic systems, incorporating single-agent and multi-agent reasoning patterns.
• Implement agent tool-calling and orchestration with internal systems such as JIRA, static analysis tools, CI/CD, and metadata services.
• Design context management pipelines (MCP-style patterns, memory, retrieval) tailored for task-specific agent reasoning.
• Apply prompt engineering, guardrails, and evaluation techniques to ensure reliable, auditable, and deterministic automation.

Python Automation & Backend Engineering

• Develop and maintain Python services, scripts, and APIs to support AI-driven automation.
• Implement asynchronous, event-driven, or batch workflows, considering scale and latency requirements.
• Build lightweight integration APIs, with a preference for FastAPI/Flask.

Systems Integration & DevOps

• Package and deploy services using Docker and Kubernetes within enterprise environments.
• Integrate with CI/CD pipelines to enable continuous testing and safe rollout processes.
• Optimize systems for scalability, resilience, and cost-efficiency.
• Implement comprehensive logging, tracing, and metrics for robust observability and debugging.

Collaboration & Engineering Excellence

• Collaborate closely with security, static analysis, and platform teams to automate manual workflows.
• Participate actively in design and architecture reviews, producing clear and concise technical documentation.
• Mentor junior engineers on Python automation and AI agent best practices.

Required Qualifications

• 3+ years of experience with a Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proficiency in multiple programming languages, including Python, Java, and C++.
• Strong expertise in automation tools and CI/CD pipelines (e.g., Jenkins, Azure DevOps, GitHub Actions).
• Proven experience in AI/ML application development and deployment.
• Solid understanding of cloud platforms and container orchestration (e.g., Azure, AWS, Kubernetes).
• Excellent problem-solving, communication, and leadership skills.

Preferred Skills

• Experience with data engineering and big data technologies.
• Knowledge of security best practices in software development.
• Familiarity with DevOps culture and tools.
• Program Analysis:
• Automate build instantiation and generate artifacts such as dependency graphs.
• Work with static and dynamic analysis tools (e.g., CodeQL, Klocwork, fuzzing frameworks) to identify vulnerabilities.
• Contribute to security-focused automation pipelines.