Full Stack Engineer

Project Role : Full Stack Engineer
Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset.
Must have skills : Large Language Models (LLMs)
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary:
As a Full Stack Engineer, a typical day involves designing, building, and refining comprehensive system features that span from the user interface to the backend infrastructure. This role requires engaging with various stages of the development lifecycle to create seamless and efficient solutions. The engineer collaborates with cross-functional teams to integrate innovative technologies, ensuring that the delivered products meet client needs and enhance service quality. Embracing a cloud-first and agile approach, the workday is dynamic, balancing coding, problem-solving, and continuous improvement to address complex business challenges effectively.

Roles & Responsibilities:
- Expected to perform independently and become an SME.
- Required active participation/contribution in team discussions.
- Contribute in providing solutions to work related problems.
- Collaborate with stakeholders to gather requirements and translate them into technical specifications.
- Maintain and improve existing systems by identifying areas for enhancement and implementing necessary changes.
- Support junior team members by sharing knowledge and providing guidance to foster professional growth.
- Ensure adherence to best practices in coding, testing, and deployment to maintain high-quality standards.
- Apply approved AI coding assistants to LLM integration and evaluation code for generation, refactoring, debugging, and unit/integration testing. Validate prompts, retrieval, structured outputs, and tool interactions for correctness, security, hallucination risk, dependency risk, and performance before release protect client data and retain human review accountability.

Professional & Technical Skills:
- Must To Have Skills: Proficiency in Large Language Models (LLMs).
- Experience with designing scalable and maintainable software architectures.
- Strong understanding of cloud computing principles and agile development methodologies.
- Ability to integrate front-end and back-end components effectively to deliver cohesive solutions.
- Familiarity with debugging, performance tuning, and optimizing complex systems.
- Capability to adapt to emerging technologies and apply them to solve real-world problems.
- Knowledge of Capital Markets and Investment Management, with experience across securities, trading, portfolio management, investment operations, and related financial services processes.
- AI Technical Skills: Hands-on use of approved coding assistants (for example, GitHub Copilot) with context-rich prompting, generated-code review, and automated test validation. Ability to integrate and evaluate LLM APIs, manage context and token budgets, implement structured outputs, retrieval-augmented generation (RAG), and controlled tool/function calling, and assess when prompt design, retrieval, or fine-tuning is appropriate. Evaluate groundedness, hallucination risk, response quality, latency, cost, prompt-injection resistance, and sensitive-data handling. AI tech stack: Python or project-approved application languages, LLM SDKs/APIs, embedding models, retrieval/vector stores, and evaluation tooling framework examples include LangChain or LlamaIndex. Framework and platform choices are project-dependent.
- Managerial Skills: Plan and coordinate LLM integration and evaluation workstreams, estimates, task allocation, dependencies, and stakeholder communication track model-quality and delivery risks, manage release readiness, and guide team knowledge sharing.
- Architectural Skills: Design LLM application and inference architectures, model/API selection, context management, retrieval, and controlled tool interfaces define evaluation, fallback, security, observability, and versioning patterns, and assess prompt, retrieval, fine-tuning, latency, and cost trade-offs.


Additional Information:
- The candidate should have minimum 3 years of experience in Large Language Models (LLMs).
- This position is based at our Hyderabad office.
- A 15 years full time education is required.

15 years full time education

About Accenture

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.

Visit us atwww.accenture.com

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