Assistant Manager

LatentView Analytics · Bangalore

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Last observed by our collector: 8 October 2026 at 11:39 pm IST. This is not a manual review or a confirmation from the employer.

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Collected role description

Job SummaryWe are seeking a highly skilled Dev ops Engineer / Platform Engineer to help build, deploy, operate, and integrate AI-powered applications and services in a production environment. This role sits at the intersection of software engineering, platform engineering, AI infrastructure, and data engineering.The ideal candidate will have strong hands-on expertise in Python, Kubernetes, Docker, backend development, APIs, CI/CD, and production systems, along with an understanding of AI/LLM applications and data engineering fundamentals. The candidate should have strong technical fundamentals, be comfortable working across application and infrastructure layers, and be able to quickly learn and adapt to evolving technologies and project requirements.Key Responsibilities<ul><li>Build and maintain backend services and APIs supporting AI-powered applications.</li><li>Develop integrations between applications, services, databases, and data systems.</li><li>Containerize and deploy applications using Docker and Kubernetes.</li><li>Develop, maintain, and improve CI/CD pipelines and deployment workflows.</li><li>Support application deployment, monitoring, reliability, troubleshooting, and production operations.</li><li>Work closely with engineering teams to improve scalability, reliability, performance, and operational efficiency.</li><li>Integrate AI agents and LLM-powered applications with backend services, APIs, and enterprise data sources.</li><li>Develop and maintain data integrations and pipelines based on evolving project requirements.</li><li>Troubleshoot issues across application, infrastructure, platform, and data layers.</li><li>Contribute to engineering standards, automation, documentation, and operational best practices.</li></ul>Qualifications & Experience<ul><li>4–10 years of professional software engineering experience with strong hands-on development experience.</li><li>Strong proficiency in Python and experience building production-grade software applications.</li><li>Hands-on experience developing backend services, APIs, and system integrations.</li><li>Strong understanding of software engineering fundamentals, including Git, testing, debugging, API development, and production software practices.</li><li>Strong hands-on experience with Kubernetes and container orchestration.</li><li>Strong experience with Docker and containerized applications.</li><li>Experience deploying, operating, and troubleshooting production applications.</li><li>Good understanding of Kubernetes concepts including workloads, deployments, services, configuration, resource management, and troubleshooting.</li><li>Experience developing and managing CI/CD pipelines.</li><li>Familiarity with monitoring, logging, observability, and production troubleshooting.</li><li>Strong SQL skills and experience working with structured and semi-structured data.</li><li>Understanding of ETL/ELT concepts, databases, data integration, and data pipelines.</li><li>Hands-on experience or familiarity with LLM applications, AI agents, RAG, tool/function calling, or AI application deployment.</li><li>Strong problem-solving skills with the ability to work across software, infrastructure, AI, and data layers.</li><li>Strong communication and collaboration skills with the ability to work effectively with cross-functional engineering teams.</li></ul>Preferred Skills & Domain Expertise<ul><li>Experience with Kubernetes at scale and production-grade platform environments.</li><li>Experience with Infrastructure as Code (IaC) tools such as Terraform or equivalent.</li><li>Understanding of distributed systems and microservices architectures.</li><li>Experience with workflow orchestration and automation frameworks.</li><li>Exposure to major cloud platforms such as AWS, Azure, or GCP.</li><li>Experience with data processing frameworks and large-scale data pipelines.</li><li>Familiarity with event-driven architectures and streaming technologies.</li><li>Experience with observability, distributed tracing, and monitoring platforms.</li><li>Understanding of security, IAM, and production platform security practices.</li><li>Exposure to AI/ML infrastructure and AI application deployment.</li><li>Familiarity with agent orchestration frameworks and LLM application architectures.</li><li>Experience working with distributed data systems, databases, and enterprise data platforms.</li></ul>Why Join Us?<ul><li>Opportunity to work on AI-powered applications and modern cloud-native platforms.</li><li>Work at the intersection of AI, software engineering, platform engineering, and data engineering.</li><li>Opportunity to work with modern technologies including Python, Kubernetes, Docker, LLMs, AI agents, and cloud platforms.</li><li>A culture that encourages innovation, continuous learning, engineering excellence, and automation.</li><li>Collaborative and dynamic environment where engineers can work across application, infrastructure, AI, and data technologies.</li></ul>We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

Collected experience requirement

4 - 8 Years