Job Description

About Paladin Tech
At Paladin Tech, we build AI-powered products that transform complex data into actionable insights. Our portfolio includes market-leading solutions for deepfake detection, video and image analytics, big data intelligence, and real-time decision support systems. We are on a mission to help organizations enhance security, verify authenticity, and drive measurable results through the strategic application of cutting-edge AI, ML, and Big Data Analytics.
Job Summary
As the Engineering Manager for our Full-Stack & AI/ML teams, you will be the technical cornerstone for our innovative product suite. We are looking for a leader who not only manages people and projects but also actively drives our technological evolution. You will be responsible for guiding a cross-functional team to build, scale, and maintain our AI-powered platforms (DeepGaze, Phonetic AI, Intellex, etc.). This role requires a strategic thinker who can translate business goals into a technical roadmap, foster a culture of excellence, and ensure our products consistently maintain a competitive edge by leveraging the latest advancements in technology.
Requirements
Key Responsibilities

• Team Leadership & Development: Lead, mentor, and scale a high-performing team of Full Stack and AI/ML engineers. Foster a culture of ownership, innovation, and continuous improvement through coaching and performance management.

• Technical Strategy & Architecture: Drive the end-to-end technical strategy, architecture, and execution for multiple AI-driven products. Ensure solutions are built for security, scalability, and cost-efficiency on cloud and hybrid infrastructures.

• Execution & Delivery: Oversee the entire product development lifecycle using agile methodologies. Manage project timelines, resource allocation, and technical risks to ensure timely and high-quality delivery.

• Technological Innovation: Champion innovation by continuously evaluating emerging AI/ML, full-stack, and infrastructure trends. Proactively identify opportunities and translate research into actionable strategies to ensure our products remain ahead of the competitive curve.

• Cross-Functional Collaboration: Partner closely with product management, data science, and senior leadership to align on the technical roadmap, define product requirements, and communicate progress to stakeholders.

• Engineering Excellence: Establish and enforce best-in-class engineering practices, including rigorous code reviews, automated testing, and robust CI/CD pipelines.

• Talent Acquisition: Own the hiring process for your team--from sourcing and interviewing to onboarding--to attract and retain top-tier engineering talent.

Core Qualifications

• 8+ years of professional software engineering experience, with at least 3+ years in a direct people management role responsible for performance reviews, mentorship, and hiring.

• Proven expertise in architecting and delivering complex systems with a deep understanding of either Full-Stack development or AI/ML, coupled with strong proficiency in the other.

• Full-Stack: Experience with modern frameworks and languages (e.g., RUST, Python, Node.js, React/Next.js) and designing microservices architecture.

• AI/ML: Hands-on experience with the ML lifecycle, including data pipelines, model training, and deploying models (especially in computer vision or NLP) into production environments.

• Proficiency in designing and managing scalable infrastructure on at least one major cloud platform (AWS, GCP, or Azure), including expertise in containerization (Docker, Kubernetes).

• Demonstrated success in leading agile development teams and managing the full product lifecycle from concept to deployment.

• A strategic mindset with the technical depth to guide architectural decisions, perform effective code reviews, and unblock your team without being a primary individual contributor.

• Excellent communication, problem-solving, and stakeholder management skills.

Preferred Qualifications

• Direct experience in domains like deepfake detection, video/image analytics, or big data intelligence platforms.

• Exposure to building AI assistants or enterprise-grade decision support tools.

• Background in cybersecurity, threat intelligence, or other regulated industries.

• Proven success in scaling engineering teams in a fast-paced startup environment.

Skills Required