About the Role
As a Senior Associate at Emplay, you'll take on responsibilities beyond basic task completion. You'll lead individual use cases, review the work of Associates, and directly engage with clients to ensure successful delivery of agentic AI solutions. This role involves a blend of technical problem-solving, workflow design, hands-on AI automation, mentoring, and guiding junior team members.
You will be responsible for transforming business requirements into scalable AI copilots powered by LLMs, RAG pipelines, and agent orchestration frameworks. You'll also play a key role in quality control, backlog management, and client-facing delivery.
This position is ideal for those who have mastered the fundamentals of AI solutioning and are now seeking opportunities for ownership, leadership, and deeper technical specialization.
Educational Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
- Postgraduates (MBA, M.Tech, M.Sc.) with relevant experience in technology, analytics, or AI are encouraged to apply.
- Certifications or coursework in AI/ML, Python, SQL, or prompt engineering are strongly preferred.
Key Responsibilities
- Use Case Leadership: Own end-to-end delivery of small-to-medium AI automation use cases.
- Quality Control & Review: Review Associates’ outputs, providing constructive feedback for accuracy, completeness, and business alignment.
- Solution Design & Debugging: Translate requirements into agent workflows, prompts, and data pipelines. Support debugging and resolve technical gaps.
- Prompt Engineering & Flow Building: Collaborate on multi-turn conversation design, fallback logic, and prompt optimization.
- Backlog & Timeline Management: Maintain sprint hygiene, track progress, and ensure timely delivery.
- Client Engagement: Serve as the primary contact for use case-level discussions, requirement clarification, and testing feedback loops.
- Exploring New Tech: Research new AI tools, libraries, or frameworks (e.g., LangChain, LangGraph, vector DBs) and share adoption opportunities.
- Mentorship: Guide Associates and Interns in execution, accountability, and best practices.
- Hiring & Training: Participate in interviews, onboarding, and training programs for new team members.
Required Skills & Qualifications
- 2–4 years of experience in Business Analyst, Solution Consultant, Product Analyst, or AI Automation Engineer roles within SaaS or enterprise software.
- Demonstrated ability to translate business needs into functional workflows and technical specs.
- Proficiency in SQL for data validation and extraction.
- Working knowledge of Python (pandas, numpy) for analysis, scripting, and debugging.
- Strong understanding of BI reporting – ability to interpret trends, anomalies, and actionable insights.
- Familiarity with LLMs, prompt design, RAG architectures, and multi-agent orchestration.
- Exposure to solution architecture diagrams and systems integration flows.
- Strong communication skills; comfortable leading client discussions.
Preferred Qualifications
- Hands-on exposure to LangChain, LangGraph, or vector databases (pgvector, Pinecone, Weaviate).
- Prior experience in consulting, enterprise delivery, or cross-functional product roles.
- Experience mentoring junior team members or leading small workstreams.
What You’ll Gain
- Ownership of end-to-end AI automation use cases with client visibility.
- Opportunity to mentor junior engineers and grow into Team Lead or Solution Architect roles.
- Deeper expertise in LLM-driven agentic workflows, multi-agent design, and AI copilots.
- Exposure to cross-vertical enterprise use cases spanning sales, procurement, and marketing.
- A chance to directly influence product direction by experimenting with new tools and frameworks.
