Senior GenAI Developer / Agentic AI Engineer

Solugenix is a leader in IT services, delivering cutting-edge technology solutions, exceptional talent, and managed services to global enterprises. With extensive experse in highly regulated and complex industries, we are a trusted partner for integrating advanced technologies with streamlined processes. Our solutions drive growth, foster innovation, and ensure compliance—providing clients with reliability and a strong competitive edge. Recognized as a 2024 Top Workplace, Solugenix is proud of its inclusive culture and unwavering commitment to excellence. Our recent expansion, with new offices in the Dominican Republic, Jakarta, and the Philippines, underscores our growing global presence and ability to offer world-class technology solutions. Partnering with Solugenix means more than just business—having a dedicated our financial client focused on your success in today's fast-evolving digital world Job Title: Senior GenAI Developer / Agentic AI Engineer Job Location: Hyderabad/Indore Experiences: 4-6 Years Shift Timings: 11:30AM-8:30PM We are looking for an experienced Senior GenAI Developer / Agentic AI Engineer to design, build, and deploy enterprise-scale AI agents, copilots, and intelligent automation solutions. The ideal candidate will have strong expertise in Agentic AI, Python development, LLM integration, AI evaluation, cloud-native architectures, and enterprise deployments. Mandatory Skills (Must Have) Candidates must have strong hands-on experience in : Agentic AI development with strong Python expertise AWS SageMaker Amazon CloudWatch LangChain CI/CD pipelines and deployment automation Key Responsibilities Agentic AI & Conversational Solutions Design and develop AI agents and multi-agent workflows. Build enterprise-grade chatbots and AI copilots. Implement agent orchestration, tool-calling, and workflow automation. Integrate AI solutions with enterprise systems, APIs, and data sources. LLM Integration & Prompt Engineering Develop and optimize prompts for business use cases. Evaluate and integrate models such as Claude, GPT, Sonnet, and enterprise-hosted LLMs. Manage model upgrades, migrations, and performance tuning. Improve agent reasoning, accuracy, and response quality. AI Platform & Enterprise Integration Integrate with AI platforms, Model Hubs, and enterprise services. Develop MCP (Model Context Protocol) servers and tool integrations. Build reusable APIs and AI services using Python/FastAPI. Support platform migrations and AI modernization initiatives. AI Testing & Benchmarking Build automated AI testing and regression frameworks. Define and track AI quality metrics: Accuracy Latency Hallucination Rate Response Consistency Cost Efficiency Establish benchmarking and evaluation processes. Integrate quality gates into CI/CD pipelines. Observability, Governance & Compliance Implement application monitoring and observability. Configure CloudWatch logging, dashboards, and alerts. Develop auditing and compliance APIs. Support responsible AI, governance, and security requirements. DevOps & Production Support Deploy AI solutions into production environments. Build and maintain CI/CD pipelines. Monitor application performance and reliability. Troubleshoot production issues and optimize system performance. Required Technical Skills AI / GenAI Agentic AI LangChain LangGraph Semantic Kernel AutoGen / CrewAI OpenAI, Azure OpenAI, Anthropic Claude RAG (Retrieval-Augmented Generation) MCP (Model Context Protocol) Programming Python (Mandatory) FastAPI REST APIs JavaScript / TypeScript (Preferred) Cloud & DevOps AWS SageMaker (Mandatory) CloudWatch (Mandatory) AWS Services Docker Kubernetes CI/CD Pipelines (Mandatory) AI Evaluation & Testing AI Benchmarking Automated Regression Testing Prompt Evaluation Model Performance Analysis Quality Metrics & Observability Data & Integration Vector Databases Elasticsearch PostgreSQL Enterprise API Integrations Preferred Qualifications Experience building enterprise AI copilots, chatbots, and agentic platforms. Experience with multi-agent architectures and orchestration frameworks. Experience integrating AI solutions into enterprise ecosystems. Strong understanding of AI governance, compliance, and Responsible AI practices. Experience with AI observability, monitoring, and production support. Ideal Candidate Profile A hands-on AI engineer with proven experience delivering Agentic AI solutions in production, strong Python development skills, expertise in AWS SageMaker, CloudWatch, LangChain, and CI/CD, and the ability to build scalable, secure, and enterprise-ready GenAI applications. Must Have & Desired Skills : In addition to the core GenAI and agentic AI responsibilities, I recommend making the following skills mandatory to ensure the candidate can contribute effectively from day one: Agentic AI with strong hands-on Python development AWS SageMaker Amazon CloudWatch LangChain CI/CD pipelines and deployment automation The role will primarily focus on: Agentic chatbot development and orchestration AI testing and benchmarking Model Hub and enterprise platform integrations MCP server development Prompt engineering and model optimization AI observability, auditing, and governance Production deployments and release management