Azentio
Senior Software Engineer-AI
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
29 September 2026
What they need
Job Title: Senior Software Engineer-AI
Years of Experience: 2-4 years
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
We are specifically looking for engineers who:
- Have built real AI applications in production environments.
- Can independently design and implement AI-driven software systems.
- Understand both AI models and enterprise software engineering.
- Are practical problem-solvers with strong execution capability.
- Can balance innovation with enterprise-grade reliability and governance.
This is not a research-only or theoretical AI role.
Candidates must demonstrate strong hands-on implementation experience with production-grade AI systems.
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, or related field.
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