• Design and develop AI applications using Amazon Bedrock • Build and configure Bedrock Agents and Action Groups • Implement Retrieval-Augmented Generation (RAG) architectures • Develop natural-language-to-API workflows • Configure Bedrock Knowledge Bases and vector search solutions • Implement AI safety controls, content filtering, and PII protection • Build and maintain serverless AWS solutions • Deploy infrastructure using Infrastructure-as-Code practices • Monitor AI system performance, usage, and operational metrics

Role Description Our AI Engineers are responsible for designing, developing, and deploying advanced Generative AI solutions to support innovative product capabilities across MyAdvice. This role focuses on building scalable AI systems, including LLM-powered pipelines, AI agents, and retrieval-augmented generation (RAG) solutions. You’ll work closely with cross-functional teams to turn business problems into intelligent, automated, and reliable AI-powered experiences. The ideal candidate is deeply hands-on with modern LLM ecosystems, can work with frameworks like LangChain and vector databases, and has experience fine-tuning and optimising foundation models, including GPT, LLaMA, Gemini and similar architectures. This position requires a strong grasp of Python, cloud platforms, MLOps processes, and production deployment standards. If you are passionate about Generative AI, constantly tinkering with new techniques, love solving complex problems, and want to build real-world AI systems at scale, you’ll thrive in this position! Essential Duties - Design, build, and deploy Generative AI applications, including chat systems, AI agents, automated workflows, and intelligent content pipelines. - Develop and maintain RAG (retrieval-augmented generation) architectures using vector stores (e.g., Pinecone, FAISS, Weaviate). - Fine-tune and evaluate large language models (LLMs), including GPT models, LLaMA, Gemini, and other modern architectures. - Implement prompt engineering strategies, prompt templates, and reusable frameworks to enhance model reliability and output quality. - Design, create, and maintain reusable AI skills, system rules, guardrails, and workflow instructions to standardize AI behavior, improve reliability, and support scalable automation across internal and client-facing AI systems. - Build end-to-end production-ready AI pipelines including data ingestion, preprocessing, training, evaluation, and continuous monitoring. - Develop tools and internal frameworks that accelerate model experimentation, evaluation, and deployment. - Integrate AI solutions into existing MyAdvice systems through REST APIs, microservices, or application middleware. - Collaborate with engineering, product, and client success teams to identify opportunities for automation and AI-powered enhancements. - Apply software engineering best practices including version control, code reviews, CI/CD, and automated testing for ML systems. - Stay current with rapid advances in AI, LLMs, multimodal models, embeddings, and MLOps technologies; propose improvements and new capabilities. - Provide technical guidance, documentation, and internal knowledge sharing related to Generative AI frameworks and production workflows. Qualifications - 1–3 years of experience in AI/ML engineering, software engineering, or a related field. - Bachelor’s degree in Computer Science, Engineering, AI/ML, or related field preferred. - Prior experience deploying AI solutions in a production or enterprise environment. - Legally authorized to work in India. - High-speed internet to support remote work. Requirements - Strong proficiency in Python (must). - Solid understanding of data structures, algorithms, and software design principles. - Experience with transformer-based LLMs and modern AI frameworks. - Hands-on with LangChain, LlamaIndex, HuggingFace Transformers, or equivalent. - Experience building RAG pipelines, embedding models, and vector database integrations. - Familiarity with AI agent frameworks and multi-step generative workflows. - Hands-on experience creating AI skills, reusable system instructions, agent rules, guardrails, and workflow-specific prompts to control and improve LLM behavior. - Experience deploying ML systems on AWS / GCP. - Proficiency with containerization: Docker, Kubernetes. - Understanding of distributed computing, model hosting, and serverless deployments. - Experience with MLOps tooling: MLflow, Weights & Biases, Sagemaker, Vertex AI, etc. - Familiarity with CI/CD pipelines, Git workflows, and testing automation for ML. - Experience working with GPT, LLaMA, Claude, Gemini or similar LLMs. - Knowledge of embeddings, tokenization, prompt engineering, and model optimization. - Experience building or contributing to production-grade AI pipelines. - Excellent written and verbal communication skills with high professionalism. - Strong attention to detail, critical thinking, and problem-solving ability. - Ability to manage multiple priorities and communicate progress effectively. - Demonstrated curiosity, adaptability, and willingness to learn cutting-edge AI innovations. Benefits - Employer-contributed medical insurance (100% premium covered by the company). - Provident Fund (PF) contributions as per policy. - Leave policy: 12 Sick/Casual Leaves + 18 Annual Leaves + 10 Company Holidays. - Remote-first Company, Flexible Schedules + Early Out Fridays! - Employee Assistance Program (EAP): free mental health support, financial/legal consultations, and more. - Tuition Reimbursement Program (up to ₹1 lakh annually) + Executive Mentorship Program. - Leadership Training Program: learn the fundamentals of leading a team (available to all employees). - Ongoing personalized coaching and career development support. - Casual / Business Casual dress code and a fun work environment (games, coffee, snacks, etc.). - Core value initiatives: “Pay It Forward,” Project Fantastic (client collaboration), and more!

• Strategic Account Ownership • Drive AI Infrastructure Revenue • Customer-Centric Engagement • Trusted Advisor • Collaborate for Success • Sales Process Excellence & Operational Hygiene • AI Ecosystem Engagement

• lead the product marketing strategy for Cisco’s AI infrastructure portfolio • connect technical capabilities to the business outcomes customers require for AI workloads and AI-native applications • define the narrative, positioning, messaging, launch strategy, and sales enablement required to power secure, connected, AI-ready organizations • partner with Product Management, Engineering, Sales, Corporate Marketing, Analyst Relations, and Communications • translate sophisticated infrastructure innovation into market value • drive cross-functional alignment • equip the business to win with enterprise buyers and executives