Generative AI Developer, Engineer, Analyst

SS&C Technologies

. Design, develop, and optimize applications leveraging internal LLM platforms .

Posted 11/11/2026full-timeRemote • IndiaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and developing Generative AI applications, with a strong focus on prompt engineering, data analysis, and integration of LLMs into enterprise systems. Proficient in building scalable architectures and ensuring compliance with security and governance standards.

Highest-signal resume keywords

Generative AI SolutionsPrompt EngineeringData AnalysisAPI IntegrationLLM Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative AIPrompt EngineeringData AnalysisEnd-to-End Application DevelopmentREST APIsRAG ArchitecturesVector SearchData ValidationApplication ArchitectureBusiness Analysis

Soft Skills

Strong Written English Skills

Tools & Technologies

Internal LLM PlatformsWeb FrameworksService-Oriented ArchitectureAutomation ToolsBlue Prism RPA

Industry Keywords

Enterprise SecurityComplianceGovernance StandardsDocument-Heavy DomainsRegulated Environments

Tech Stack

Tools & technologies

RPA

About the role

Key responsibilities & impact

Design, develop, and optimize applications leveraging internal LLM platforms
Create, test, and maintain high-quality prompts
Apply few-shot prompting, prompt chaining, and RAG
Establish prompt evaluation and versioning practices
Build full-stack, end-to-end GenAI applications
Design and implement backend services integrating LLMs with enterprise systems
Develop or collaborate on web-based user interfaces
Integrate GenAI capabilities into existing applications and workflows
Work with REST APIs, web frameworks, and backend services
Build scalable, maintainable application architectures
Analyze structured and unstructured data for GenAI use cases
Translate business requirements into LLM-driven workflows
Perform data validation, transformation, and analysis for AI pipelines
Collaborate with automation teams
Build solutions aligned with enterprise security, compliance, and governance standards
Work with private/internal LLMs to ensure data privacy and controlled usage
Document design decisions, prompts, and system behavior

Requirements

What you’ll need

2–3 years of hands-on experience in Generative AI / LLM-based solutions
2–3 years of experience in data analysis, business analysis, or analytics-driven roles
1–3 years of experience in prompt engineering
Strong written English skills
Ability to code in at least one modern programming language
Experience building end-to-end applications
Experience with internal/private LLM platforms
Experience with RAG architectures and vector search
Experience with APIs and service-oriented architecture
Understanding of LLM limitations, including hallucinations, bias, and drift
Understanding of evaluation and validation of model outputs
Understanding of cost, latency, and performance trade-offs
Preferred/nice-to-have: Blue Prism RPA experience
Preferred/nice-to-have: Experience with enterprise web applications
Preferred/nice-to-have: Familiarity with LLMOps/MLOps concepts
Preferred/nice-to-have: Knowledge of document-heavy domains
Preferred/nice-to-have: Experience in regulated or enterprise environments

Benefits

Comp & perks

Production-grade Generative AI applications
Secure, internal LLM platforms
Opportunity to influence responsible GenAI adoption at scale
End-to-end engineering team environment