Java AWS Kubernetes Devops Ai at MNC · Mumbai · 8 - 10 years · ₹7L - ₹15L / yr · Posted 9 Oct 2026

Job Title: Java AWS Kubernetes DevOps AI/ML
Experience: 8–10 Years
The candidate should have at least 1 year of experience in AI/ML and hands-on experience with the below technologies:
Java
AWS
Kubernetes
DevOps
AI/ML
MongoDB / PostgreSQL
Key-Value Caching
Vector Databases – ChromaDB / Pgvector

Similar jobs (10)
- Bachelor’s degree in computer science, Data Science, Information Systems, or a related field
- 8-10 years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering
- Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure
- Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn
The Role
As a **DevOps Engineer** you'll own the infrastructure and delivery backbone that
keeps our platform running as we grow. You'll build the CI/CD, cloud infrastructure, and
observability that let a small, fast-moving team ship confidently — and you'll keep our AI and
data workloads reliable and affordable at scale.
This is a hands-on role with real ownership: you won't be maintaining someone else's setup,
you'll be shaping ours. You'll work closely with the backend, AI/ML, and data teams to make
deployment boring, incidents rare, and scaling a non-event. ---
What You'll Own
**CI/CD & developer experience**
- Build and maintain fast, reliable CI/CD pipelines so engineers ship multiple times a day with
confidence. - Make the path from commit to production simple, safe, and repeatable, with sensible
automated testing, rollbacks, and release controls.
**Cloud infrastructure & IaC** - Own our cloud infrastructure (AWS/GCP) end to end, managed as code (Terraform or
similar) — no click-ops. - Design for scale and cost-efficiency as store and conversation volumes grow.
**Containers & orchestration** - Run our services on containers/Kubernetes: deployments, autoscaling, networking, and
resource management. - Support the specific needs of AI/ML workloads, including GPU-backed inference and batch
processing for the speech pipeline.
**Reliability & observability (SRE)** - Own uptime, performance, and incident response — monitoring, logging, tracing, alerting,
on-call, and blameless postmortems. - Define and defend SLOs; keep the platform dependable as it scales across clients.
**Data & pipeline infrastructure** - Support the infrastructure behind large-scale, edge-to-cloud data movement and
processing (audio ingestion, ASR/AI pipelines, analytics). - Keep data workloads reliable, performant, and cost-aware.
**Security & compliance** - Bake security into the platform: secrets management, IAM/least-privilege, encryption in
transit and at rest, network hardening, and vulnerability management. - Support compliance readiness (including India's DPDP Act and enterprise-client security
requirements) for a product that handles sensitive customer conversations.
**Cost & scale** - Own cloud cost visibility and optimization; make scaling decisions that balance reliability
and spend. ---
What You'll Bring - 6+ years in DevOps, SRE, platform, or infrastructure engineering, running production
systems at meaningful scale. - Strong hands-on experience with a major cloud provider (**AWS or Azure or GCP**) and
Infrastructure-as-Code (**Terraform** or equivalent). - Solid experience with **containers and Kubernetes** in production. - Experience building and owning **CI/CD** pipelines (e.g. GitHub Actions, GitLab CI,
Jenkins, Argo, or similar).
- Comfort with a scripting/automation language (Python, Go, or Bash) and a strong
automation-first mindset. - Real experience with **observability** (Prometheus/Grafana, ELK, Datadog,
OpenTelemetry, or similar) and running incident response / on-call. - A security-conscious approach — secrets, IAM, encryption, and least-privilege as defaults. - Startup temperament: ownership, pragmatism, and a bias to automate and ship. - Based in or willing to relocate to Bangalore, and up for an onsite/hybrid, in-person team.
Bonus Points - Experience running **ML/AI or GPU workloads** in production (inference serving, batch
pipelines, model deployment). - Experience with data-intensive infrastructure — streaming/queues (Kafka, SQS), data
pipelines, or large object/audio storage. - Exposure to **edge devices / IoT fleets**, OTA updates, or high-volume device-to-cloud
ingestion. - Experience with compliance/security frameworks (SOC 2, ISO 27001, DPDP). - FinOps / cloud cost-optimization experience. - Early-stage startup experience. ---
Why Join - Own infrastructure that's already live with leading retail brands and growing fast — real
scale, real impact. - Work across genuinely interesting workloads: speech AI, GPU inference, large-scale data,
and edge-to-cloud ingestion. - Small team, high ownership, direct line to engineering leadership — your decisions ship. - Build the platform foundation of a category-defining product from an
Job Title : DevOps Engineer / Site Reliability Engineer (SRE)
Experience : 4+ Years
Location : Gurugram, Sector 48, Haryana (On-site)
Employment Type : Full-Time
Working Days : Monday to Saturday (1st & 3rd Saturday Off)
About the Role :
We are looking for a hands-on DevOps Engineer / Site Reliability Engineer (SRE) with strong experience in Linux, AWS, Kubernetes, Docker, CI/CD, Infrastructure as Code, and production application deployments.
The ideal candidate should have real-world production experience, excellent troubleshooting skills, and the ability to manage both infrastructure and application-level issues.
Mandatory Skills :
Linux, AWS, Docker, Kubernetes, Terraform, Ansible, Jenkins, GitHub Actions, GitLab CI/CD, CI/CD, Infrastructure as Code (IaC), Python, Bash, Git, Grafana, Prometheus, ELK, CloudWatch, New Relic, SRE (SLI/SLO/SLA), Networking (DNS, HTTP/HTTPS, TCP/IP, Load Balancer), Production Application Deployment & Troubleshooting
Key Responsibilities :
- Manage and maintain AWS cloud infrastructure.
- Build and optimize CI/CD pipelines using Jenkins, GitHub Actions, or GitLab CI.
- Deploy, monitor, and troubleshoot applications across production environments.
- Automate infrastructure using Terraform and Ansible.
- Manage Docker containers and Kubernetes clusters.
- Monitor systems using Grafana, Prometheus, ELK, CloudWatch, and New Relic.
- Perform Linux server administration and troubleshooting.
- Handle production incidents, Root Cause Analysis (RCA), and improve system reliability.
- Collaborate with development teams to support application releases and automation.
Required Qualifications :
- Bachelor's degree in Computer Science or related field.
- 4+ years of hands-on experience in DevOps / SRE.
- Strong Linux administration and production troubleshooting skills.
- Experience with AWS and modern DevOps toolchains.
- Hands-on experience with application deployment and production support.
What We're Looking For :
- Strong practical Linux and cloud knowledge.
- Real production experience with application deployments.
- Ability to troubleshoot both infrastructure and application issues.
- Experience handling live production incidents.
- Excellent communication and problem-solving skills.
- Candidates should be comfortable with scenario-based technical discussions and demonstrate genuine hands-on expertise.
Interview Process :
- HR Screening
- Technical Round
- Client Technical Round
- Final Discussion
Note : The interview will focus on practical hands-on experience in Linux, AWS, Kubernetes, Docker, CI/CD, Infrastructure as Code, application deployment, production troubleshooting, and real-world DevOps scenarios.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Job Description:
Pre-requisite skills required for a DevOps Engineer role include:
- 6+yrs exp in DevOps
- Experience working on Linux based infrastructure
- knowledge in AWS, docker, CI/CD tools
- Hands on exp in Python/shell scripting language
- hands on exp in AWS and Azure
- Work exp in Docker, Terraform, Ansible, Kubernetes, LINUX
- Excellent understanding of Ruby, Python, Perl, and Java
- Configuration and managing databases such as MySQL, Mongo
- Excellent troubleshooting
- Working knowledge of various tools, open-source technologies, and cloud services
Job Title : Senior AWS DevSecOps & AI Platform Engineer
Experience Required : 5+ Years in AWS / Cloud Engineering
Terraform Experience : 4+ Years
Location : Gurugram
Work Mode : Onsite
Employment Type : Full-time
About the Role :
We are looking for an experienced Senior AWS DevSecOps & AI Platform Engineer with strong expertise in AWS cloud infrastructure, Kubernetes, Infrastructure as Code (IaC), CI/CD automation, cloud security, and database administration.
The ideal candidate will be responsible for designing and maintaining secure, scalable, reliable, and cost-efficient cloud environments while supporting microservices-based applications and implementing DevSecOps best practices. The role also involves building and deploying AI agents using Amazon Bedrock and Bedrock AgentCore, along with managing enterprise development and collaboration tools.
Mandatory Skills :
AWS (EC2, EKS, ECS, Lambda, S3, CloudWatch), Kubernetes, Terraform, Jenkins, Bitbucket Pipelines, CI/CD, DevSecOps, AWS Security Services (IAM, WAF, GuardDuty, Security Hub, KMS, Secrets Manager), Microservices, Helm, PostgreSQL, Oracle SQL, RDS, Jira, Confluence, Amazon Bedrock, Bedrock AgentCore, AWS Networking, and Cloud Cost Optimization.
Key Responsibilities :
- AWS Cloud Infrastructure : Design, implement, and maintain AWS infrastructure with a focus on scalability, availability, security, reliability, and cost optimization.
- Microservices & Containerization : Manage and support distributed microservices architectures, including deployment, monitoring, troubleshooting, performance optimization, service meshes, and API gateways.
- Kubernetes Administration : Administer and optimize Kubernetes clusters, including Amazon EKS and self-managed environments, covering upgrades, networking, workload management, scaling, and resource optimization.
- Cloud Security & Compliance : Implement and manage AWS security services, including IAM, GuardDuty, Security Hub, WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
- DevSecOps Implementation : Integrate security testing, vulnerability scanning, container security, and compliance-as-code tools into CI/CD pipelines.
- CI/CD & Source Control : Manage Bitbucket repositories, branching strategies, permissions, and Bitbucket Pipelines. Build and optimize Jenkins pipelines using declarative and scripted approaches.
- Infrastructure as Code : Develop and maintain Terraform modules, manage remote state and workspaces, detect infrastructure drift, and implement reusable infrastructure provisioning practices.
- Database Administration : Provision, manage, secure, and optimize AWS RDS databases, particularly PostgreSQL and Oracle, including backups, replication, patching, performance tuning, and migrations.
- Jira & Confluence Administration : Manage projects, workflows, automation rules, permissions, user access, spaces, schemes, and plugins.
- Monitoring & Reliability : Define and monitor SLIs, SLOs, and SLAs; implement observability best practices; and participate in incident management, root cause analysis, and post-incident reviews.
- AI Agent Development : Design, build, and deploy AI agents using Amazon Bedrock and Bedrock AgentCore, including agent runtime, memory, tools, gateway integration, identity and access management, guardrails, and lifecycle management across environments.
- Cloud Connectivity : Support hybrid cloud connectivity using AWS Direct Connect, VPN, and Transit Gateway.
- Cost Optimization : Apply FinOps practices to monitor cloud expenditure, optimize resource utilization, and improve infrastructure efficiency.
- API Integrations : Integrate third-party APIs while implementing authentication, rate limiting, error handling, and webhook management.
Required Skills & Qualifications :
- 5+ years of hands-on experience with AWS cloud services, including EC2, ECS, EKS, Lambda, ALB, CDN, S3, CloudWatch, Amazon Bedrock, and Bedrock AgentCore.
- Strong understanding of AWS networking, multi-account strategies, landing zone architecture, and hybrid connectivity.
- 4+ years of practical experience with Terraform, including module development, remote state management, workspaces, drift detection, and state operations.
- Extensive experience administering Kubernetes, preferably Amazon EKS, including Helm, Kustomize, operators, RBAC, network policies, autoscaling, and multi-tenancy.
- Proven experience managing distributed microservices, service meshes, API gateways, and inter-service communication.
- Strong knowledge of AWS security services, including IAM, Service Control Policies (SCPs), WAF, KMS, Secrets Manager, AWS Config, and CloudTrail.
- Experience implementing least-privilege access, zero-trust principles, and cloud security compliance controls.
- Hands-on experience integrating DevSecOps tools such as Snyk, Trivy, Checkov, and SonarQube into CI/CD pipelines.
- Understanding of OWASP security principles, CIS benchmarks, vulnerability management, and container security.
- Proficiency in Bitbucket repository administration, branch permissions, and YAML-based Bitbucket Pipelines.
- Strong experience developing and maintaining Jenkins CI/CD pipelines, shared libraries, plugins, and build agents.
- Experience administering AWS RDS databases, particularly PostgreSQL and Oracle SQL, including backup, replication, performance tuning, and migration activities.
- Experience administering Jira and Confluence, including workflows, permissions, automation, and plugin management.
- Working knowledge of Azure services, particularly Web Apps and Logic Apps/Workflows.
- Practical experience with Amazon Bedrock, including model invocation, guardrails, and AI agent development and deployment using Bedrock AgentCore.
- Understanding of third-party API integration, authentication mechanisms, rate limiting, error handling, and webhook management.
- Familiarity with FinOps practices and cloud cost optimization.
Good-to-Have Skills :
- Additional Azure experience, including networking, Azure SQL Managed Instance, and Azure Kubernetes Service (AKS).
- Hands-on experience with AI-driven Development Lifecycle (AI-DLC) methodologies and tools such as Kiro.
Relevant certifications, such as :
- AWS Certified Solutions Architect
- AWS Certified DevOps Engineer – Professional
- AWS Machine Learning or Generative AI certifications
- Certified Kubernetes Administrator (CKA)
- HashiCorp Terraform certifications
Ideal Candidate Profile :
The ideal candidate is a hands-on cloud and DevSecOps professional who can manage enterprise-scale AWS infrastructure, automate deployments, strengthen security controls, troubleshoot complex distributed systems, and support AI agent development. Strong problem-solving skills, an automation-first mindset, and the ability to collaborate across development, security, and infrastructure teams are essential.
Join our product development team at Planview as a Senior Software Engineer I and become a pivotal force on the Viz Core Team. This role offers the unique opportunity to shape and lead the development of data-processing pipelines and APIs that are at the heart of our software solutions. These solutions are designed to streamline and enhance the efficiency of software delivery, resonating deeply with software engineers who strive to build better and faster.
At Planview Viz, which is powered by the innovative “Flow Framework,” you will tackle complex data challenges and develop scalable solutions within an AWS cloud environment. Your efforts will be crucial in revolutionizing how businesses harness and interpret vast amounts of workflow data, transforming it into actionable insights that propel organizational efficiency and effectiveness.
Responsibilities (What you'll do)
- Create and refine powerful data-processing architectures that integrate seamlessly with a diverse array of external tools, enhancing the way software is delivered across industries.
- Drive operational excellence by critically analyzing problems, defining requirements, and devising robust solutions that push the boundaries of technology.
- Lead and inspire a team of talented engineers, promoting a culture of ownership, meticulous attention to quality, and proactive problem-solving.
- Stay at the cutting edge of technology by updating and expanding your team’s knowledge of cloud architectures, data processing, and advanced analytics, ensuring that you and your team remain leaders in technological innovation.
- Make a direct impact on the efficiency and effectiveness of software delivery worldwide through innovation and leadership.
Qualifications (What you'll bring)
Who We’re Looking For
The ideal candidate is a seasoned professional in cloud software development with a strong foundation in data processing and scalable software systems. You thrive in collaborative environments and are passionate about advancing cloud technology and data architecture to new heights. You are a leader who enjoys mentoring, guiding, and inspiring others.
Preferred Qualifications
Skills, Knowledge, and Expertise
- A degree in Computer Science, Engineering, or a related field.
- 6+ years of experience with a modern programming language, with a focus on back-end systems and cloud-based technologies.
- Strong capability in architecting and designing robust, scalable software systems.
- Proficiency in AWS or another popular cloud platform.
Additional Qualifications
- Experience with big-data technologies such as Spark and Apache Kafka.
- Experience with Java (version 17), Scala, or other JVM programming languages.
- Experience with tools such as Amazon Redshift and MongoDB.
- Experience with continuous integration and continuous deployment tools such as GitHub, Jenkins, Travis CI, or similar platforms.
- Proficiency in test-driven development.
- Experience with containers and orchestration tools such as Kubernetes.
- Experience working on remote or distributed teams and projects.
Company Overview:
Planview is hiring a DevOps Engineer in Bengaluru, India to support Planview SaaS applications across the product line. You will work in a global, collaborative team — owning CI/CD pipelines, cloud infrastructure, and automation to keep deployments fast and systems reliable.
Responsibilities
- Build and maintain CI/CD pipelines in Jenkins for reliable, fast delivery.
- Manage containerized workloads on Docker and ECS — task definitions, services, and clusters.
- Provision and manage AWS infrastructure using Terraform (CloudFormation a plus).
- Automate configuration and deployment tasks using Python (Ansible a plus).
- Set up and maintain monitoring and alerting via New Relic (CloudWatch, Datadog, or Prometheus/Grafana a plus).
- Write Shell and Python scripts to automate operations and reduce manual work.
- Manage Git workflows — branching, merge strategies, and pull request reviews.
- Administer and support MSSQL databases underpinning the product line — backups, restores, and basic performance troubleshooting.
- Troubleshoot deployment, performance, and infrastructure issues with development teams.
- Participate in on-call rotations and drive incident response.
- Continuously improve infrastructure resilience and deployment speed.
- Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.
Qualifications
Must-Have Skills
- Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
- OS: Windows administration (systemd, package management, log analysis).
- Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
- Source Control: Git — branching, merge/rebase, PR reviews.
- CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
- Containerization (Docker + ECS): Task definitions, services, and clusters.
- IaC: Terraform.
- Monitoring: New Relic.
- Scripting: Bash and Python scripting for automation.
- Networking Basics: DNS, load balancers, security groups, VPNs.
- Logging: ELK stack / CloudWatch Logs.
- Database: MSSQL administration — backups, restores, basic performance troubleshooting.
- Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
- AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.
Nice-to-Have Skills
• Configuration Management: Ansible.
• Additional IaC: CloudFormation.
• Architecture: Knowledge of microservices architecture.
• Cloudflare: DNS, CDN, WAF.
• Artifact Repositories: Nexus, JFrog Artifactory, ECR.
• Other CI/CD Tools: GitHub Actions.
• AWS cost optimization / FinOps awareness.
• Datadog, CloudWatch, or Prometheus/Grafana.
• AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).
• Database Basics: RDS backups, restores, performance tuning.
Job Summary :
We are looking for a proactive and skilled DevOps Engineer to join our team and play a key role in building, managing, and scaling infrastructure for high-performance systems. The ideal candidate will have hands-on experience with Kubernetes, Docker, Python scripting, cloud platforms, and DevOps practices around CI/CD, monitoring, and incident response.
Key Responsibilities :
- Design, build, and maintain scalable, reliable, and secure infrastructure on cloud platforms such as AWS.
- Implement Infrastructure as Code (IaC) using tools like Terraform, Cloud Formation, or similar.
- Manage Kubernetes clusters, configure namespaces, services, deployments, and auto scaling. CI/CD & Release Management
- Build and optimize CI/CD pipelines for automated testing, building, and deployment of services.
- Collaborate with developers to ensure smooth and frequent deployments to production.
- Manage versioning and rollback strategies for critical deployments.
- Containerization & Orchestration using Kubernetes.
- Containerize applications using Docker, and manage them using Kubernetes.
- Write automation scripts using Python or Shell for infrastructure tasks, monitoring, and deployment flows.
- Develop utilities and tools to enhance operational efficiency and reliability.
- Monitoring & Incident Management
- Analyze system performance and implement infrastructure scaling strategies based on load and usage trends.
- Optimize application and system performance through proactive monitoring and configuration tuning.
Desired Skills and Experience :
- Experience Required - 6+ yrs.
- Hands-on experience on cloud services like AWS, EKS etc.
- Ability to design a good cloud solution.
- Strong Linux troubleshooting, Shell Scripting, Kubernetes, Docker, Ansible, Jenkins Skills.
- Design and implement the CI/CD pipeline following the best industry practices using open-source tools.
- Use knowledge and research to constantly modernize our applications and infrastructure stacks.
- Be a team player and strong problem-solver to work with a diverse team.
- Having good communication skills.
Job Specification:
Work Experience: 7 to 10 Years
Work Location: Bangalore
Mode of Employment: Permanent
Education Qualification required: Any Degree
Job Description:
We are looking for an experienced DevOps Engineer with strong expertise in Linux, CI/CD, containerization, cloud platforms, Infrastructure as Code (IaC), and observability. The ideal candidate should have hands-on experience with Kubernetes, OpenShift, Terraform, scripting, DevSecOps, and modern monitoring practices.
Responsibilities:
- Manage and maintain Linux-based systems, cloud infrastructure, and production environments.
- Develop, maintain, and optimize CI/CD pipelines using Git and related automation tools.
- Deploy and manage containerized applications using Docker, Kubernetes (K8s), and OpenShift.
- Provision and manage cloud infrastructure on AWS and/or Microsoft Azure.
- Automate infrastructure provisioning and configuration using Terraform.
- Develop automation scripts using Python and Shell scripting.
- Implement observability and monitoring solutions using Prometheus, Grafana, AppDynamics, and Splunk.
- Troubleshoot production incidents, perform root cause analysis (RCA), and improve system reliability and availability.
- Implement DevSecOps practices, security controls, and vulnerability management across CI/CD pipelines.
- Manage cloud networking, connectivity, and infrastructure-related configurations.
- Support AIOps initiatives to improve incident detection, analysis, and operational efficiency.
- Manage SSL/TLS certificates, secrets, and secure credential rotation.
Required Skills:
- Strong hands-on experience with Linux.
- Good knowledge of Git and CI/CD pipelines.
- Experience with Docker, Kubernetes (K8s), and/or OpenShift.
- Working experience with AWS and/or Microsoft Azure.
- Hands-on experience with Terraform and Infrastructure as Code (IaC).
- Scripting knowledge in Python and/or Shell.
- Experience with Prometheus, Grafana, AppDynamics, and/or Splunk.
- Knowledge of DevSecOps, networking, and cloud security fundamentals.
- Understanding of AIOps concepts and automated operations.
- Experience with certificate lifecycle management and secrets management.
Solid product experience and an educational background from Tier‑1 universities are preferred.
As a Senior AI Engineer, you will play a key role in designing and delivering highly scalable, next generation AI products within our AI stack. You will work in a technically rich environment with talented peers, contributing to product planning, design, and execution while influencing the evolution of Teradata’s AI capabilities.
In this role, you will:
- Design, develop, and maintain high quality systems, services, and applications with an emphasis on scalability, reliability, and performance.
- Collaborate with cross-functional engineers and product partners to shape design and consistently deliver end to end features.
- Build and integrate robust RESTful APIs, ensuring security, data consistency, and maintainability.
- Work with SQL and NoSQL databases to implement efficient data models and service access patterns.
- Apply and experiment with AI/ML technologies, including agentic AI and large language models (LLMs).
- Use AI powered engineering tools to improve development quality, speed, and productivity.
- Mentor engineers, supporting them in technical planning, implementation, and best practices.
- Identify and resolve system performance bottlenecks, optimizing code, design, and infrastructure.
- Write unit and integration tests and participate in code reviews to uphold engineering excellence.
- Investigate production issues, ensuring timely and effective solutions.
- Stay current with emerging trends in engineering, AI/ML, and cloud-native technologies.
Who You’ll Work With
You will be part of a high-performing engineering team building core components of Teradata’s AI platform. You will collaborate closely with other engineers, AI/ML specialists, product managers, cloud architects, and partner teams across the company. The role offers opportunities to contribute directly to Teradata’s AI product roadmap and technological direction.
What Makes You a Qualified Candidate
(Nonnegotiable qualifications)
- Bachelor’s degree in Computer Science or equivalent from a recognized institution.
- 5+ years of experience in backend services, distributed systems, or data platform development.
- Strong proficiency in Java, Go, or Python for service development.
- Good understanding of design principles, distributed system patterns, and service framework.
- Hands-on experience designing and developing RESTful APIs.
- Experience with SQL and NoSQL databases and data modelling.
- Strong debugging, problem solving, and troubleshooting skills.
- Experience with modern containerization and orchestration tools such as Kubernetes.
- Knowledge of public cloud platforms.
- Experience with AI productivity tools (e.g., GitHub Copilot).
- Ability to work independently, drive workstreams, and deliver high quality outcomes.
- Strong communication and collaboration skills.
What You’ll Bring
(Preferred qualifications)
- Familiarity with messaging systems such as Kafka.
- Experience experimenting with or implementing AI/ML technologies, Agentic AI, or LLMs.
- A track record of influencing design decisions and driving engineering best practices.
- The ability to mentor engineers and guide them through design, planning, and execution.
- A proactive mindset and comfort working in fast paced, dynamic environments.
- Curiosity, adaptability, and a passion for building impactful AI-driven products.











