Software Engineer III
First seen by Alion on Aug 21, 2026.
Title : Software Engineer III- UKG
Location : Noida/ Pune
Experience : 4-6 Years
Candidate Requirements :
- Primary Tech Stack : Java or .NET
- AI Experience : Strong hands-on experience with AI technologies is required
- Interview Availability : Candidates should be willing to attend an in person (F2F) interview at our Bangalore office on Saturday or Sunday
About the Team :
Youll join a collaborative engineering team that builds and improves full-stack software solutions for UKG products and customers. We work closely with product owners, engineers, and business partners to understand customer needs, design practical solutions, and deliver reliable software that supports real-world workforce challenges.
Responsibilities :
- Software Development : Write clean, maintainable, and efficient code for various software applications and systems.
- Technical Strategy : Drive the technical strategy and vision for major projects and initiatives, ensuring alignment with business goals and industry best practices. Communicate complex concepts, anticipate potential objections, and influence others to adopt a point of view.
- Leadership : Lead cross-functional teams to design, develop, and deliver high-impact software projects on time and within budget. Coordinate activities and tasks of other team members, working independently.
- Architectural Excellence : Architect, design, and develop complex software systems, ensuring high standards of performance, scalability, and reliability. Define architectural standards and patterns across teams.
- Complexity : Solve complex issues with innovative solutions, setting precedents. Navigate ambiguous situations and relationships to achieve results.
- Impact : Impact the achievement of area/group objectives. Develop team policies, procedures, and techniques. Drive prioritization of technical debt with articulated impact and outcomes.
- Service Health and Quality : Ensure health and quality of services and incidents, proactively identifying and addressing issues. Conduct thorough root cause analysis.
- Engineering Excellence Practices : Advocate for and implement best quality practices; hold a high bar for engineering excellence; guide the team in maintaining service quality through the testing pyramid.
- DevOps Model : Oversee CI/CD pipelines ensuring efficient build, test, and deployment phases. Own the full lifecycle from requirements through production maintenance.
- AI Technical Standards : Identify high-leverage opportunities to apply AI/ML capabilities to complex engineering problems; define technical standards and evaluation frameworks for AI-powered features across teams.
- Testing : Build testable software, define tests, automate tests using tools (e.g., JUnit, Selenium) and design patterns leveraging the test automation pyramid.
- Code Review : Conduct comprehensive code reviews, including review of AI-generated code for quality, security, and performance.
- Mentorship : Provide technical mentorship and guidance, fostering a culture of learning and continuous improvement. Mentor engineers on AI best practices and responsible AI development.
- Documentation : Develop and maintain comprehensive technical documentation for software applications and systems.
- Innovation : Stay current with emerging technologies, including AI/ML advancements, advocating for their adoption to drive innovation and productivity enhancement within the team.
Minimum Qualifications :
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
- 5+ years of professional software development experience.
- Deep expertise in one or more programming languages such as Dot NET or Java.
- Extensive experience with software architecture and design patterns, including the ability to design and implement scalable, reliable systems in a DevOps model.
- Proven track record of leading and delivering large-scale, complex software projects.
- Proficiency with cloud technologies (Azure, AWS, GCP) and version control systems (GitHub).
- Demonstrated ability to identify high-leverage opportunities to apply AI/ML capabilities to complex engineering problems; experience driving AI integration decisions across multiple teams or systems.
- Strong working knowledge of LLM integration patterns including RAG architectures, agentic frameworks, prompt engineering best practices, and output evaluation strategies with ability to establish team-wide standards.
- Experience contributing to or defining AI evaluation (eval) frameworks : defining quality metrics, failure modes, safety criteria, and production monitoring approaches for AI-powered systems.
- Proficiency in building telemetry or observability as part of the development process.
- Strong leadership, communication, and interpersonal skills.
Preferred Qualifications :
- Master's degree or PhD in Computer Science or a related technical field.
- Familiarity with developing accessible technologies.
- Demonstrated expertise in specialized disciplines. Recognized as a technical expert in their area.
- Understanding of internal and external business challenges and regulatory factors.
- Experience with MLOps practices : model deployment pipelines, versioning, A/B testing, monitoring for model drift, and cost governance for AI inference workloads at scale.
- Familiarity with LLM fine-tuning approaches (e.g., LoRA, QLoRA, RLHF) and the ability to make informed build/buy/integrate decisions for AI capabilities.
- Track record of mentoring senior engineers on AI best practices and influencing adoption of responsible AI development standards across the organization.
- Experience with agentic AI frameworks (LangChain, LlamaIndex, or equivalent) for multi-step AI workflows in production environments.
Skills
Java, .Net, Azure, System Design, Artificial Intelligence, Machine Learning, LLM, MLOps, AI Integration, Design Patterns, Backend Architecture