01Responsibilities
Design, develop, and integrate AI-powered features and solutions into enterprise applications to enhance user experience and business outcomesCollaborate with SMES, ML engineers, and product teams to operationalize machine learning models and AI services in production environmentsBuild and maintain scalable APIs and services that leverage Generative AI, Large Language Models (LLMs), and intelligent automation capabilitiesEvaluate, fine-tune, and integrate AI models and frameworks to address business use cases and improve application functionalityImplement responsible AI practices, ensuring solutions meet security, privacy, compliance, and ethical AI standardsDevelop and optimize Retrieval-Augmented Generation (RAG) solutions, vector databases, and knowledge-grounding capabilitiesMonitor AI solution performance, model quality, accuracy, and operational reliability in production environmentsStay current with emerging AI technologies, industry trends, and best practices, and recommend their adoption where appropriatePartner with stakeholders to identify opportunities for leveraging AI to improve productivity, automation, and decision-makingContribute to AI governance, model evaluation frameworks, prompt engineering practices, and AI solution architecture standardsMentor team members on AI-enabled development practices and promote the adoption of modern AI engineering approachesDesign, develop, test, and maintain scalable, reliable, and secure software applicationsLead the end-to-end delivery of complex features and projects, from requirements gathering through deployment and supportCollaborate with product managers, architects, designers, and cross-functional engineering teams to define and implement technical solutionsWrite clean, maintainable, and well-documented code following industry best practices and coding standardsConduct code reviews, provide constructive feedback, and mentor junior engineers to promote engineering excellenceTroubleshoot and resolve complex technical issues, ensuring optimal application performance and reliabilityDrive system architecture discussions and contribute to technical design decisionsImprove software quality through automated testing, CI/CD pipelines, and observability practicesParticipate in Agile development processes, including sprint planning, estimation, stand-ups, and retrospectivesContinuously evaluate and adopt new technologies, tools, and development practices to improve productivity and product qualityCollaborate with stakeholders to understand business requirements and translate them into technical solutionsEnsure compliance with security, privacy, and operational standards throughout the software development lifecycleSupport production systems, analyze root causes, and implement preventive measures for recurring issuesContribute to technical documentation, knowledge sharing, and process improvements across the engineering organizationComply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do soRequired Qualifications:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field5+ years of professional software development experienceHands-on experience with DevOps practices, CI/CD, and containerization technologiesHands-on experience with Generative AI technologies, including Large Language Models (LLMs) such as OpenAI, Azure OpenAI, Anthropic Claude, or similar platformsExperience with cloud platforms (Azure, AWS, or Google Cloud)Experience mentoring engineers and leading technical initiatives Experience building applications using AI services such as Azure AI, Azure OpenAI, Copilot technologies, or equivalent cloud-based AI platformsExperience developing and deploying AI/ML-powered applications in enterprise environmentsExperience building AI-powered solutions using Retrieval-Augmented Generation .
