Job description

We are At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20 years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000 , and has 58 offices in 22 countries within key global markets. Our challenge We are seeking a hands-on Senior AI Engineer to design, build, and deploy production-grade artificial intelligence solutions. The ideal candidate combines strong software engineering fundamentals with practical experience developing, integrating, and operating AI systems at scale. This role requires deep proficiency in Java and Python, experience with Google Cloud Platform (GCP), and a proven track record of taking AI and machine learning capabilities from concept through production. Candidate will work closely with product managers, data scientists, software engineers, and business stakeholders to deliver reliable, scalable, and measurable AI solutions. Additional Information* The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within New York, NY is $115k - $130k/year & benefits (see below). The Role Responsibilities: Design, develop, and maintain production-grade AI and machine learning applications. Build scalable backend services, APIs, data pipelines, and AI platforms using Java and Python. Develop and integrate solutions involving generative AI, machine learning models, natural language processing, recommendation systems, or other applied AI technologies. Deploy, monitor, optimize, and troubleshoot AI workloads on GCP . Work with GCP services such as Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub, Cloud Storage, Cloud Functions, and related platform technologies. Develop reliable model-serving and inference systems with a focus on performance, scalability, security, and cost efficiency. Implement production AI practices, including model versioning, evaluation, observability, drift monitoring, testing, and continuous improvement. Collaborate with data scientists and ML engineers to productionize models and integrate them into enterprise applications. Design and implement secure, maintainable, and well-tested software using modern engineering practices. Participate in architecture reviews, technical design discussions, code reviews, and engineering standards initiatives. Investigate emerging AI technologies and assess their applicability to business and product needs. Mentor engineers and contribute to the development of best practices for AI engineering and cloud-native software delivery. Requirements: 7–10 years of professional software engineering experience, including substantial experience delivering AI or machine learning solutions. Strong hands-on programming experience with Java and Python. Proven experience building and operating production AI/ML systems, not only research or proof-of-concept applications. Strong experience with Google Cloud Platform, including cloud-native application development, deployment, monitoring, and security. Experience designing and developing RESTful APIs, microservices, distributed systems, and event-driven architectures. Solid understanding of machine learning concepts, model lifecycle management, data preparation, evaluation, and inference. Experience with software engineering best practices, including: Automated testing, CI/CD ,Version control, Code quality and review, Containerization, Monitoring and observability Experience deploying applications with Docker and Kubernetes or GKE. Strong understanding of application security, scalability, reliability, and performance optimization. Ability to translate ambiguous business or product requirements into practical technical solutions. Excellent communication, collaboration, and problem-solving skills. Preferred, but not required: Experience with Vertex AI, generative AI, large language models, prompt engineering, retrieval-augmented generation, vector databases, or AI agents. Experience with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, LangChain, or equivalent technologies. Familiarity with MLOps platforms, model registries, feature stores, and automated model evaluation. Experience with BigQuery, Apache Beam, Dataflow, Dataproc, or other large-scale data processing technologies. Knowledge of responsible AI, model governance, privacy, explainability, and bias mitigation. Experience building enterprise AI applications with high availability and strict latency or security requirements. Relevant Google Cloud or machine learning certifications. We offer: A highly competitive compensation and benefits package. A multinational organization with 58 offices in 22 countries and the possibility to work abroad. 10 days of paid annual leave (plus sick leave and national holidays). Maternity & paternity leave plans. A comprehensive insurance plan including medical, dental, vision, life insurance, and long-/short-term disability (plans vary by region). Retirement savings plans. A higher education certification policy. Commuter benefits (varies by region). Extensive training opportunities, focused on skills, substantive knowledge, and personal development. On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses. Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups. Cutting edge projects at the world’s leading tier-one banks, financial institutions and insurance firms. A flat and approachable organization. A truly diverse, fun-loving, and global work culture. S YNECHRON’S DIVERSITY & INCLUSION STATEMENT Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more. All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law . Candidate Application Notice

Requirements

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Our challenge
Additional Information*
The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within New York, NY is $115k - $130k/year & benefits (see below).
Design, develop, and maintain production-grade AI and machine learning applications.
Build scalable backend services, APIs, data pipelines, and AI platforms using Java and Python.
Develop and integrate solutions involving generative AI, machine learning models, natural language processing, recommendation systems, or other applied AI technologies.
Deploy, monitor, optimize, and troubleshoot AI workloads on GCP .
Work with GCP services such as Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub, Cloud Storage, Cloud Functions, and related platform technologies.
Develop reliable model-serving and inference systems with a focus on performance, scalability, security, and cost efficiency.
Implement production AI practices, including model versioning, evaluation, observability, drift monitoring, testing, and continuous improvement.
Collaborate with data scientists and ML engineers to productionize models and integrate them into enterprise applications.
Design and implement secure, maintainable, and well-tested software using modern engineering practices.
Participate in architecture reviews, technical design discussions, code reviews, and engineering standards initiatives.
Investigate emerging AI technologies and assess their applicability to business and product needs.
Mentor engineers and contribute to the development of best practices for AI engineering and cloud-native software delivery.
7–10 years of professional software engineering experience, including substantial experience delivering AI or machine learning solutions.
Strong hands-on programming experience with Java and Python.
Proven experience building and operating production AI/ML systems, not only research or proof-of-concept applications.
Strong experience with Google Cloud Platform, including cloud-native application development, deployment, monitoring, and security.
Experience designing and developing RESTful APIs, microservices, distributed systems, and event-driven architectures.
Solid understanding of machine learning concepts, model lifecycle management, data preparation, evaluation, and inference.
Experience with software engineering best practices, including: Automated testing, CI/CD ,Version control, Code quality and review, Containerization, Monitoring and observability
Experience deploying applications with Docker and Kubernetes or GKE.
Strong understanding of application security, scalability, reliability, and performance optimization.

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aijavapythongcpmachine learningmlci/cddockerkubernetes

Platform: workday
Effort: long

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