Senior Software Engineer L7
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Job Summary
Overview
The Team is looking for an exceptional Senior Software Engineer to help build the next generation of intelligent agentic applications and engineering platforms. This is a high-impact role for a hands-on engineer who combines deep software engineering expertise with a passion for AI innovation and practical problem solving.
You will design and build scalable production-grade systems that leverage AI agentic workflows and modern developer tooling to accelerate product delivery and improve engineering productivity across the full product development lifecycle. You will work at the intersection of software engineering AI capability development developer experience and platform innovationturning emerging technologies into secure reliable and reusable capabilities that create measurable business value.
We are looking for someone who is curious entrepreneurial and energized by solving hard problems. The ideal candidate brings strong ownership analytical thinking and a continuous-learning mindset and is excited to explore new tools challenge conventional approaches and raise the bar for how modern software is built.
This is a hands-on role for an engineer who is deeply engaged in applying agentic patterns to real products platforms and developer workflows. You will help create the services frameworks and reusable engineering patterns that enable teams across our client to experiment faster deliver with confidence and scale AI-enabled solutions responsibly
Requirements
Position Responsibilities:
As a Senior Software Engineer you will:
Design build and evolve intelligent agentic applications and platform capabilities that solve meaningful business problems at scale
Apply AI and agentic development patterns to improve engineering productivity across design coding testing debugging documentation release engineering and operational support
Use modern tools and coding assistants thoughtfully to accelerate delivery while maintaining strong standards for quality security reliability and maintainability
Partner with product data science and engineering teams to translate ideas into production-grade solutions with clear business impact
Drive technical innovation by evaluating emerging tools frameworks and engineering practices and identifying where they can create differentiated value
Build reusable frameworks services and internal developer capabilities that improve developer experience and reduce delivery friction across teams
Lead by example through hands-on engineering sound technical judgment and a strong bias for execution and ownership
Solve complex technical problems with creativity analytical rigor and a pragmatic approach to trade-offs and delivery
Improve software development lifecycle efficiency through automation AI-assisted workflows and engineering excellence
Ensure AI-enabled systems are production-ready observable secure governable and resilient in enterprise environments
Influence architecture engineering standards and best practices for building scalable modern applications in cloud-native ecosystems
Continuously learn experiment and help elevate team capability in emerging AI and software engineering techniques
Ideal Candidate Qualifications:
7 years of strong software engineering experience building scalable maintainable production-grade systems
Hands-on experience building applications or platforms using Generative AI or agentic design patterns
Strong understanding of agent orchestration tool use prompt and context management memory patterns evaluation and AI system design trade-offs
Experience taking AI-enabled solutions from prototype to production with sound engineering discipline across reliability observability latency cost security and governance
Practical experience using AI coding and engineering assistants to improve productivity across the software development lifecycle
Experience improving PDLC and SDLC efficiency through automation CI/CD automated testing and AI-assisted engineering workflows
Strong programming skills in one or more backend languages such as Java and Python with the ability to write high-quality well-tested production-ready code
Experience building services in cloud-native environments using Kubernetes and managed cloud services on AWS Azure
Good understanding of APIs distributed systems event-driven architectures data pipelines and enterprise integration patterns
Experience with modern AI frameworks SDKs and tools for building AI applications agent workflows and developer productivity solutions
Strong problem-solving and analytical skills with the ability to break down ambiguity and turn ideas into practical scalable solutions
Demonstrated innovative mindset with curiosity to learn new technologies evaluate emerging tools and apply them where they create value
Strong sense of ownership and accountability with the ability to independently drive initiatives from concept to delivery
Excellent collaboration and communication skills with experience working across engineering product AI and business stakeholders
Experience with modern front-end frameworks such as React and/or is beneficial
Familiarity with inference APIs embeddings retrieval-augmented generation model evaluation and AI safety controls is preferred
All About You
You thrive on building innovative products platforms and engineering capabilities that solve real-world problems at scale
You are hands-on highly curious and energized by learning new tools technologies and ways of working
You actively leverage AI tooling to enhance productivity improve quality and accelerate software delivery
You bring a strong ownership mindset and take accountability for outcomes not just tasks
You are a creative and analytical problem solver who can navigate ambiguity and turn complex challenges into elegant solutions
You are excited by the opportunity to build and scale agentic applications and AI-enabled engineering capabilities in real production environments
You balance speed with engineering discipline and care deeply about security resilience quality and maintainability
You have a product mindset and care about user impact developer experience and continuous improvement
You communicate clearly collaborate effectively across functions and help raise the bar for those around you
You enjoy experimenting challenging assumptions and helping shape the future of modern software engineering
Must-Have | Strong proficiency in Java Python or similar backend languages; Hands-on experience building agentic or AI-enabled applications; Strong understanding of APIs distributed systems event-driven architectures and enterprise integration patterns Experience with React or Experience with cloud-native development using Kubernetes and managed cloud platforms such as AWS or Azure Experience with CI/CD automation and engineering productivity tooling; Familiarity with modern AI frameworks SDKs and tools for building intelligent applications and agent workflows |
Good to Have | Practical use of AI coding assistants to improve delivery speed and quality; Familiarity with LLM orchestration prompt and context management memory patterns inference APIs embeddings retrieval-augmented generation vector databases model evaluation AI observability and responsible AI controls. |
Required Skills:
Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. Understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understands the concept of region and AZs. Provide L2 support production systems like application database middleware components infrastructure and network components. Manage production incidents end-to-end within defined SLAs with focus on resolution rather than who caused it. Interact with various stakeholders such as Release managers program leads service managers development and test leads Review operational readiness requirements such as monitoring and alerting log rotation and resilience of the components and report the gaps Provide pre-implementation support with activities such as release notes review and implementation dry runs. Protect production components by running health checks monitoring latency and memory utilization. Automate day-to-day activities and propose changes that improve reliability Participate in CAB and provide feedback on change requests Support the DevOps team in testing the promoted pipelines and suggest automation of configuration items. Practice incident management best practices and perform RCA. Participate in disaster recovery tests and operational acceptance tests Analyze the technology stack that makes up the product and optimize recovery time objective. Work with team members spread across and time zones Share knowledge document improvements and mentor junior resources It is good to have skills using Jenkins to orchestrate builds and link to Sonar Maven etc. to build out the CI/CD pipeline. Support deployments of code into multiple lower environments. Supporting current processes needed with an emphasis on automating everything as soon as possible. It is good to have skill to design Implement and enhance our deployment automation based on Chef. We need proven experience designing and implementing an overall release and deployment process. It is good to have skill to design and implement a Git based code management strategy that will support multiple environment deployments in parallel. Experience with automation for Branch management code promotions and version management. Engage in and improve the whole lifecycle of servicesfrom inception and design through deployment operation and refinement. Requirements MQ/EB Understanding of event-driven architectures Distributed systems - How clusters are formed Quorum management Failure handling. 3 to 5 years of hands-on Experience in MQ or NATS broker or similar messaging solutions. An understanding of Kafka clustering would be good to have. Knows Client-Server communication aspects - sockets TLS protocol etc Understand the concept of region and AZs. Deployments MTF/Prod Maintenance items (including stop/start Disaster Recovery-related activities etc.) CR for changes in MTF/Prod Good knowledge on Nginx Tools - Log Monitoring Tool - Splunk Application Monitoring tool - Dynatrace Ticketing incident/problem management tool - Remedy Dev-ops Basics - CI-CD Basics Overview of Git Bit-bucket SonarQube Ansible/Chef Skills - Linux & Shell Scripting ITIL / ITSM PL/SQL Troubleshooting Jenkins - CI/CD Groovy Scripting/Yaml Ansible/Chef Nginx Java / JEE Event-Driven Architectures MQ or NATS broker or similar messaging solutions. Kafka Client-server communication aspects - sockets TLS protocol Understand the concept of region and AZs.
