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Job Title: AI Senior Engineer Years of Experience: 2 to 4 Location: Bangalore Role Overview We are looking for highly skilled and hands-on AI Engineers to design and build next-generation AI Agents for enterprise banking applications. The ideal candidate should possess strong software engineering fundamentals combined with practical experience in building AI-driven systems using modern language models, conversational AI, intelligent automation, and explainable AI techniques. This role requires engineers who can architect and implement enterprise-grade AI solutions not just experiment with theoretical AI concepts. Candidates must have real-world experience designing scalable, secure, explainable, and production-ready AI systems in regulated environments. The selected engineers will work on building intelligent banking agents capable of: Conversational interactions Observational and event-driven reasoning Workflow orchestration Decision support Context-aware automation Enterprise integrations Key Responsibilities Design and develop AI Agents for banking and financial services applications. Build conversational AI systems for banking workflows. Develop observational and autonomous agents capable of monitoring events, learning patterns, and triggering intelligent actions. Design AI-powered enterprise software solutions with strong focus on scalability, explainability, auditability, and security. Work with Small Language Models (SLMs) and enterprise-grade learning models for domain-specific banking use cases. Build AI architectures that support human-in-the-loop workflows and responsible AI principles. Integrate AI models with enterprise systems, APIs, workflow engines, databases, and banking platforms. Collaborate with product managers, architects, domain experts, and engineering teams to deliver production-grade AI applications. Implement model monitoring, evaluation, explainability, and governance mechanisms. Optimize AI systems for latency, performance, accuracy, and cost efficiency. Participate in architecture reviews, technical design discussions, and proof-of-concept initiatives. Required Skills & Experience Core AI & Engineering Skills Strong hands-on experience in designing and developing AI-powered applications. Experience with: Conversational AI AI Agents Autonomous/Observational Agents Retrieval-Augmented Generation (RAG) Prompt Engineering Agentic workflows AI orchestration frameworks Practical experience working with: Small Language Models (SLMs) Large Language Models (LLMs) Fine-tuning and model optimization Strong software engineering and system design capabilities. Experience building enterprise-grade distributed systems. Programming & Technology Stack Strong hands-on experience in: Python Java or Node.js REST APIs and microservices AI/ML frameworks and libraries Vector databases and semantic search Cloud platforms (AWS/Azure/GCP) Containerization and orchestration (Docker/Kubernetes) AI Frameworks & Tools Experience with one or more: LangChain LlamaIndex CrewAI AutoGen Semantic Kernel Hugging Face Open-source model ecosystems Explainability & Responsible AI Experience building explainable and auditable AI systems. Understanding of: Explainable AI (XAI) AI governance Responsible AI Model evaluation frameworks Bias mitigation AI security and compliance Enterprise Experience Experience delivering AI solutions in enterprise environments. Banking, fintech, or regulated industry experience preferred. Strong understanding of scalable architecture, security, compliance, and operational resilience. Preferred Qualifications Experience in banking or financial services domain. Exposure to loan processing, payments, treasury, risk, compliance, fraud detection, or customer servicing platforms. Experience integrating AI with enterprise banking software platforms. Familiarity with MLOps and AI lifecycle management. Exposure to knowledge graphs, intelligent workflows, or multi-agent systems. Understanding of data privacy and regulatory requirements in banking. What We Are Looking For W .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.