AI Engineer

Detailed job description - Skill Set:
• Lead the design and delivery of the agentic AI platform and prioritized agent roadmap for S2 2026, ensuring alignment with the committed portfolio, enterprise architecture standards, and measurable business outcomes
• Conduct a comprehensive assessment of the current Launch application enhancement backlog and identify opportunities where AI agents, automation, or generative AI capabilities can deliver significant productivity, quality, or user-experience improvements
• Partner closely with Launch Digital stakeholders, business SMEs, and technical teams to define, develop, and deploy AI-enabled solutions that address business needs and deliver measurable operational efficiencies
• Collaborate with the Infosys Launch ecosystem development team to evaluate existing application functionality, identify opportunities for rationalization or retirement enabled by new AI capabilities, and develop recommendations supported by business value, user impact, and technical feasibility analyses
• Develop business cases, implementation roadmaps, and success metrics for proposed AI solutions, ensuring clear prioritization and value realization
• Provide technical leadership and guidance on agent architecture, orchestration frameworks, data integration, governance, security, and responsible AI practices


Mandatory Skills


Education:

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative field.

Mandatory Skills

1. 3+ years of hands-on experience in AI/ML, Generative AI, intelligent automation, or agentic AI solutions.
2. Proven expertise in Python and AI/ML frameworks (MLFlow, TensorFlow, PyTorch, Scikit-learn, LangChain, or equivalent).
3. Strong background in data analysis, business process assessment, and large-scale data-driven decision making.
4. Experience with data engineering, feature engineering, and data processing libraries (Pandas, NumPy, Spark).
5. Demonstrated experience in designing and deploying AI-powered applications, agents, or automation solutions.
6. Experience with LLMs, semantic search, embeddings, RAG, or vector-based retrieval methods.
7. Deep understanding of AI architectures, orchestration frameworks, enterprise integrations, governance, security, and responsible AI principles.
8. Experience with MLOps practices and tools (model versioning, experiment tracking, pipeline orchestration).
9. Proficiency in SQL and working with large enterprise datasets.
10. Strong problem-solving and analytical skills with the ability to evaluate complex business and technology challenges.
11. Excellent communication skills; ability to explain AI concepts to both technical and non-technical stakeholders.
12. Ability to collaborate effectively with cross-functional business and technology teams.

Preferred Skills

1. Experience assessing application backlogs and identifying AI, automation, or GenAI opportunities.
2. Experience in training, fine-tuning, and optimizing machine learning and foundation models.
3. Experience with Agentic AI frameworks, prompt engineering, and workflow orchestration.
4. Experience developing business cases, implementation roadmaps, and value realization metrics.
5. Experience with semantic indexing, vector databases, and enterprise knowledge retrieval solutions.
6. Familiarity with data visualization and analytics tools (Tableau, Power BI, Looker, etc.).
7. Background in AI, NLP, information retrieval, or intelligent automation.
8. Experience working on AI, digital transformation, or innovation-focused teams.

Nice-to-Have Skills

1. Experience in enterprise AI transformation, platform modernization, or application rationalization initiatives.
2. Knowledge of microservices architectures, event-driven systems, APIs, and CI/CD pipelines.