company_site
Regular AI Engineer
Luxoft
Bengaluru, IND
Full-time
Mid · 5+ years experience
Onsite
Discovered 1 weeks ago
MUST be with computer science academic background Must have 5+ years of experience as a AI Engineer by using Python o Full-stack development with strong Python expertise and API design capabilities o Hands-on experience with GenAI frameworks and tools (LangChain, LlamaIndex, Semantic Kernel, OpenAI API, Azure OpenAI or equivalent) o Understanding of AI agent orchestration and communication protocols (MCP, function calling, tool use) o Knowledge of data modelling, vector databases and RAG architectures o Containerization and orchestration (Docker, Kubernetes) in enterprise environments o CI/CD pipeline design and MLOps practices o Familiarity with cloud platforms (Azure preferred) and private cloud banking infrastructure o Understanding of IT workflows, software development lifecycle and DevOps practices — ability to identify where AI adds the most value o Proven track record of adapting open-source Large Language Models (LLMs) via techniques like LoRA, QLoRA, and full parameter fine-tuning is a plus o Advanced knowledge of Hugging Face libraries (transformers, peft, accelerate, datasets) for model training, evaluation, and deployment is a plus
Key Skills for This Role
MUST be with computer science academic background Must have 5+ years of experience as a AI Engineer by using Python o Full-stack development with strong Python expertise and API design capabilities o Hands-on experience with GenAI frameworks and tools (LangChain, LlamaIndex, Semantic Kernel, OpenAI API, Azure OpenAI or equivalent) o Understanding of AI agent orchestration and communication protocols (MCP, function calling, tool use) o Knowledge of data modelling, vector databases and RAG architectures o Containerization and orchestration (Docker, Kubernetes) in enterprise environments o CI/CD pipeline design and MLOps practices o Familiarity with cloud platforms (Azure preferred) and private cloud banking infrastructure o Understanding of IT workflows, software development lifecycle and DevOps practices — ability to identify where AI adds the most value o Proven track record of adapting open-source Large Language Models (LLMs) via techniques like LoRA, QLoRA, and full parameter fine-tuning is a plus o Advanced knowledge of Hugging Face libraries (transformers, peft, accelerate, datasets) for model training, evaluation, and deployment is a plus
Full Job Posting
Responsibilities
- Design, develop and deploy Generative AI solutions (AI assistants, code generation tools, intelligent automation) that increase APS productivity - Collaborate with IT teams across the domains to identify high-impact use cases where AI can streamline development, testing, documentation or operations - Build AI agent architectures tailored to IT workflows, including agent orchestration and inter-agent communication protocols (e.g. Model Context Protocol – MCP) - Develop full-stack components supporting AI solutions: backend services (Python – mandatory), frontend interfaces, and API layers - Collaborate and Leverage the Group AI offering solutions and services (eg,: LLMaaS, RAGaaS, Data tools, etc.), APIs and components to build solutions efficiently while providing feedback for platform improvements - Implement and maintain CI/CD pipelines for AI solution deployment, ensuring quality, reproducibility and traceability - Design and manage containerized environments (Kubernetes/Docker) for AI workloads in the bank's private cloud infrastructure - Ensure all solutions comply with the bank's security, data privacy and governance standards, particularly around sensitive data handling and regulatory constraints - Conduct proof-of-concepts (PoCs) and prototyping to evaluate emerging AI tools and frameworks for potential adoption in IT use cases - Proactively identify opportunities for standardization, process improvement, deployment optimization, resilience enhancement, and innovation across cloud AI operations.
- Design, develop and deploy Generative AI solutions (AI assistants, code generation tools, intelligent automation) that increase APS productivity
- Collaborate with IT teams across the domains to identify high-impact use cases where AI can streamline development, testing, documentation or operations
- Build AI agent architectures tailored to IT workflows, including agent orchestration and inter-agent communication protocols (e.g. Model Context Protocol – MCP)
- Develop full-stack components supporting AI solutions: backend services (Python – mandatory), frontend interfaces, and API layers
- Collaborate and Leverage the Group AI offering solutions and services (eg,: LLMaaS, RAGaaS, Data tools, etc.), APIs and components to build solutions efficiently while providing feedback for platform improvements
- Implement and maintain CI/CD pipelines for AI solution deployment, ensuring quality, reproducibility and traceability
- Design and manage containerized environments (Kubernetes/Docker) for AI workloads in the bank's private cloud infrastructure
- Ensure all solutions comply with the bank's security, data privacy and governance standards, particularly around sensitive data handling and regulatory constraints
- Conduct proof-of-concepts (PoCs) and prototyping to evaluate emerging AI tools and frameworks for potential adoption in IT use cases
- Proactively identify opportunities for standardization, process improvement, deployment optimization, resilience enhancement, and innovation across cloud AI operations.
SKILLS
- Must have
- MUST be with computer science academic background Must have 5+ years of experience as a AI Engineer by using Python o Full-stack development with strong Python expertise and API design capabilities o Hands-on experience with GenAI frameworks and tools (LangChain, LlamaIndex, Semantic Kernel, OpenAI API, Azure OpenAI or equivalent) o Understanding of AI agent orchestration and communication protocols (MCP, function calling, tool use) o Knowledge of data modelling, vector databases and RAG architectures o Containerization and orchestration (Docker, Kubernetes) in enterprise environments o CI/CD pipeline design and MLOps practices o Familiarity with cloud platforms (Azure preferred) and private cloud banking infrastructure o Understanding of IT workflows, software development lifecycle and DevOps practices — ability to identify where AI adds the most value o Proven track record of adapting open-source Large Language Models (LLMs) via techniques like LoRA, QLoRA, and full parameter fine-tuning is a plus o Advanced knowledge of Hugging Face libraries (transformers, peft, accelerate, datasets) for model training, evaluation, and deployment is a plus
- Nice to have
- o Genuine passion and intellectual curiosity for AI, Generative AI and emerging technologies o Strong problem-solving and analytical skills with a solution-oriented mindset o Clear and effective communication skills, able to articulate complex technical concepts to non-technical stakeholders o Ability to collaborate and work effectively in a distributed, multi-cultural team environment o Attention to detail and rigor, particularly around code quality, testing and documentation o Proactive and autonomous, able to drive initiatives with minimal supervision while respecting governance frameworks
Qualifications
- Must have
- o Genuine passion and intellectual curiosity for AI, Generative AI and emerging technologies o Strong problem-solving and analytical skills with a solution-oriented mindset o Clear and effective communication skills, able to articulate complex technical concepts to non-technical stakeholders o Ability to collaborate and work effectively in a distributed, multi-cultural team environment o Attention to detail and rigor, particularly around code quality, testing and documentation o Proactive and autonomous, able to drive initiatives with minimal supervision while respecting governance frameworks
Preferred Qualifications
- MUST be with computer science academic background Must have 5+ years of experience as a AI Engineer by using Python o Full-stack development with strong Python expertise and API design capabilities o Hands-on experience with GenAI frameworks and tools (LangChain, LlamaIndex, Semantic Kernel, OpenAI API, Azure OpenAI or equivalent) o Understanding of AI agent orchestration and communication protocols (MCP, function calling, tool use) o Knowledge of data modelling, vector databases and RAG architectures o Containerization and orchestration (Docker, Kubernetes) in enterprise environments o CI/CD pipeline design and MLOps practices o Familiarity with cloud platforms (Azure preferred) and private cloud banking infrastructure o Understanding of IT workflows, software development lifecycle and DevOps practices — ability to identify where AI adds the most value o Proven track record of adapting open-source Large Language Models (LLMs) via techniques like LoRA, QLoRA, and full parameter fine-tuning is a plus o Advanced knowledge of Hugging Face libraries (transformers, peft, accelerate, datasets) for model training, evaluation, and deployment is a plus
- Nice to have
- o Genuine passion and intellectual curiosity for AI, Generative AI and emerging technologies o Strong problem-solving and analytical skills with a solution-oriented mindset o Clear and effective communication skills, able to articulate complex technical concepts to non-technical stakeholders o Ability to collaborate and work effectively in a distributed, multi-cultural team environment o Attention to detail and rigor, particularly around code quality, testing and documentation o Proactive and autonomous, able to drive initiatives with minimal supervision while respecting governance frameworks
About Luxoft
Technology10,001+Founded 2000
Global IT services and consulting company
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