Description :
We're looking for an Engineering Manager to lead a team of backend and AI engineers building high-performance, scalable systems that power our next-generation [product / platform]. You'll drive technical excellence, mentor engineers, and collaborate closely with product, data science, and DevOps teams to deliver robust backend services and intelligent AI-powered solutions.
The core responsibilities for the job include the following :
Leadership and Management :
- Lead, mentor, and grow a team of backend and AI engineers.
- Foster a culture of ownership, innovation, and technical excellence.
- Collaborate with cross-functional teams (Product, Data Science, ML Ops, and Infrastructure) to align technology efforts with business goals.
- Conduct regular 1 : 1s, performance reviews, and technical development plans.
Technical Delivery :
Oversee the design and development of scalable backend architectures, APIs, and microservices.Guide the integration of AI / ML models into production systems, ensuring performance, reliability, and maintainability.Establish best practices for code quality, testing, deployment, and observability.Collaborate on system design, architecture decisions, and technical roadmaps.Balance engineering velocity with technical debt management and system reliability.AI Development Oversight :
Work closely with AI / ML teams to bring research and prototypes into production.Define and manage infrastructure requirements for model training, serving, and monitoring.Ensure data pipelines and APIs support machine learning workflows efficiently.Stay current with emerging AI frameworks, cloud services, and backend technologies.Requirements :
10+ years of hands-on backend development experience.2+ years of experience leading or managing engineering teams.Strong expertise in one or more backend technologies : Python, Go, Java, or Node.js .Experience with NLP and generative AI libraries : Hugging Face Transformers, LangChain, OpenAI API, RAG pipelinesExperience with LLMs (Large Language Models) prompt engineering, fine-tuning, and inference optimization.Proven experience designing distributed systems, APIs, and microservices (e. g., using gRPC, REST, Kafka, or GraphQL).Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized environments (Docker, Kubernetes).Solid understanding of software architecture, DevOps practices, and CI / CD pipelines.Excellent communication and leadership skills.(ref : hirist.tech)