Quest Global
From Quest Global's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible.
Job Requirements
At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster.
As Engineering Lead for our P&DI data products, you'll own the technical strategy behind our AI-enabled insights-first platforms — and the team that builds them. You will:
Set the technical strategy, architecture, and roadmap across data pipelines, ML services, the agent layer, and the governance layer (PII masking, audit trace, guard-railed execution) — and push reusable, scalable components across every deployment.
A hands-on engineer with the ability to independently design, develop, deploy, and maintain scalable software solution that includes backend services, APIs, and microservices to support AI-driven applications.
Build and deploy cloud-native applications using Docker, Kubernetes, and modern cloud infrastructure.
Develop full-stack applications, including responsive web interfaces, backend APIs, and integration services.
Design and implement distributed systems that support asynchronous processing, concurrent workloads, and real-time communication.
Good understanding of distributed systems, system design, load balancing, caching, and message-driven architectures.
Integrate existing AI models, LLM services, and agentic frameworks into enterprise applications.
Develop reusable platform components, API gateways, workflow orchestration services, and integration frameworks.
Implement and manage Kubernetes workloads, including deployment, scaling, networking, service discovery, and resource optimization.
Build and maintain CI/CD pipelines and automate infrastructure provisioning, application deployment, and operational workflows.
Implement authentication, authorization, API security, secrets management, and secure communication between services.
Establish monitoring, logging, distributed tracing, and alerting to ensure application reliability and performance.
Identify and resolve performance bottlenecks, infrastructure issues, and production incidents.
Collaborate with architects, Data Scientists, AI engineers, and product teams to translate technical requirements into production-ready solutions.
Contribute to system architecture, technical documentation, code reviews, and engineering best practices.
Scout emerging technologies and turn the promising ones into production-ready capability.
Drive responsible AI through governance, security, model evaluation, risk management, and compliance with customer and enterprise standards.
Architect for deployment inside customers' own networks — zero dependency on third-party AI services — with resiliency and business continuity built in.
Mentor engineers and technical leads, raising the bar on AI literacy and technical excellence.
Act as a strategic thought partner to business and technology leaders — challenge the status quo, and reset priorities as the landscape shifts.
A bachelor's degree from a reputed university; an advanced technical degree is a plus.
10–12 years hands-on experience in software development, cloud engineering, or platform engineering, including 3–4+ years leading a team or technical track.
Strong programming skills in Python, with experience in frameworks such as FastAPI, Flask, or Django.
Experience with backend development, RESTful APIs, microservices, and asynchronous programming.
Proficiency in JavaScript/TypeScript and frontend frameworks such as React or Next.js with component libraries such as Tailwind CSS.
Strong hands-on experience with Docker and Kubernetes, including container orchestration, deployment, networking, and scaling.
Understanding of GPU infrastructure, resource scheduling, and AI inference workload management.
A track record designing, building, and running enterprise-scale applications — production infrastructure, deployment architectures (on-prem, private cloud, or AWS/GCP/Azure), resiliency, and business continuity.
Experience with infrastructure automation and deployment tools such as Terraform, Helm, and CI/CD pipelines.
Good understanding of distributed systems, system design, load balancing, caching, and message-driven architectures.
Familiarity with messaging and caching technologies such as Kafka, RabbitMQ, or Redis.
Experience implementing authentication and authorization using OAuth 2.0, OpenID Connect, JWT, or similar standards. Also, experience with identity and access management platforms such as Keycloak.
Familiarity with Generative AI applications, LLM APIs, and AI inference services. Exposure to agentic AI architectures, tool calling, and the Model Context Protocol (MCP).
Experience with relational databases such as PostgreSQL or MySQL, Clickhouse, along with exposure to NoSQL databases and vector databases.
Familiarity with observability and monitoring tools such as Prometheus, Grafana, OpenTelemetry, or ELK Stack.
Strong understanding of Linux environments, networking fundamentals, Git, and software development best practices.
Grounding in Responsible AI principles, governance frameworks, and model risk management.
Fluency in Git and CI/CD, with sharp debugging and problem-solving instincts.
We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.
We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.
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