Please mention DailyRemote when applying
See how much of this job your resume covers, and what’s missing.
Want a recruiter to go through it line by line?
Get professional reviewOne click makes a copy of your resume for this role, scores it against the posting, and proposes edits line by line. Your default resume is never changed.
Upload your resume and we draft a letter for this exact role, tailored to what it asks for.
You will own the technical delivery, configuration, and integration of client workstreams while translating business requirements into practical technical specifications. Additionally, you will build and validate data pipelines and support the deployment process through various testing stages to production.
About SymphonyAI Financial Services
SymphonyAI Financial Services is on a mission to make the financial system safer. We combine more than 25 years of financial crime expertise with advanced AI to help financial institutions detect risk, fight financial crime, and navigate an increasingly complex regulatory environment.
We are reimagining financial crime compliance around connected risk intelligence, agent led workflows, and embedded governance, helping institutions strengthen controls, reduce manual effort, and adapt as risks evolve.
About The Role
Successful client onboarding depends on reliable technical delivery, clear communication, and the ability to solve complex integration problems. That’s where you come in.
As a Technical Consultant, you’ll own technical configuration, deployment, and integration for assigned client workstreams across SaaS and client-hosted environments. You’ll translate business and regulatory requirements into practical technical specifications, build and validate data pipelines, and support delivery through SIT, UAT, OAT, and production deployment.
You’ll work day-to-day with client compliance, risk, and technology teams, as well as Technical Program Managers, Data Science, and Engineering. This is a hands on, client-facing role where you’ll use logs, data, automation, and root cause analysis to keep implementations moving, make risks visible, and deliver production-ready solutions.
Responsibilities
• Own technical delivery. Lead configuration, deployment, integration, and data pipeline activities for assigned client workstreams from requirements through OAT and production.
• Translate requirements into solutions. Turn client business, regulatory, data, and security needs into clear technical specifications and implementation plans.
• Build reliable data pipelines. Develop, validate, orchestrate, and deploy SQL- and Python-based pipelines with appropriate data quality checks, scheduling, documentation, and operational readiness.
• Configure and deploy applications. Use GitHub, YAML, Helm, Kubernetes, and CI/CD practices to package, configure, and deploy solutions across SaaS and client environments.
• Solve problems at the source. Use logs and root cause analysis to resolve moderately difficult issues across data, APIs, SAML/SSO, networking, deployment, and application configuration.
• Support client acceptance. Plan and support SIT, UAT, OAT, technical reviews, validation, and production deployment while protecting delivery timelines, SLA commitments, and client acceptance.
• Put AI to work. Use AI tools, LLMs, and RAG to accelerate technical workflows, pipeline development, validation, documentation, and troubleshooting while checking outputs for accuracy and suitability.
• Integrate AI capabilities. Support model endpoints, data preparation, and AI or LLM API integration through REST endpoints or SDKs, and help monitor deployed AI solutions.
• Partner across teams. Work closely with client stakeholders, Technical Program Managers, Solution Architects, Data Science, Engineering, and Product Delivery on decisions, risks, and scope.
• Make progress visible. Provide proactive status updates on delivery, dependencies, risks, issues, and technical decisions to project sponsors and senior stakeholders.
• Help others grow. Share implementation practices and mentor junior consultants while escalating architecture changes and material scope decisions to the appropriate senior owners.
You may be a good fit if you have
• 3 to 7 years of technical implementation experience with hands on delivery in enterprise or client-facing environments, including at least one deployment through UAT or one data pipeline delivered to production.
• Strong SQL and data skills. You can build queries and pipelines, perform data validation and quality checks, and troubleshoot database or data integration issues.
• Linux/Unix and scripting experience using Bash and the ability to read and troubleshoot Python, Java, or similar code.
• Deployment and automation experience with Git, GitHub, CI/CD, YAML, Helm, and working knowledge of Kubernetes.
• Integration experience with XML and JSON configuration, REST APIs, SAML/SSO, and basic networking concepts.
• Cloud experience with at least one major platform such as AWS, Azure, or GCP.
• Strong problem solving skills. You use logs, evidence, and root cause analysis to resolve integration, deployment, data, and environment issues.
• Client-facing communication skills. You can explain complex technical topics clearly, manage stakeholder expectations, and provide proactive updates on progress, risks, and issues.
• An ownership mindset. You can manage an assigned workstream end to end, balance multiple priorities, and escalate architecture or scope changes at the right time.
• Practical AI experience. You have used AI tools or LLM APIs to accelerate technical work and understand the importance of validating outputs before integrating them into business processes.
Strong candidates may also have
• Hands-on experience with AML, KYC, fraud, sanctions, transaction monitoring, alert management, or other compliance platforms.
• Experience with Spark, Snowflake, or another enterprise data platform.
• Experience with pipeline orchestration, scheduling, production monitoring, and data quality frameworks.
• Exposure to ML model deployment, model endpoints, feature preparation, or monitoring for data drift and model degradation.
• Experience with GraphQL, microservices, rule engines, or complex enterprise integrations.
• A cloud certification in AWS, Azure, or GCP.
• Experience working with global enterprise clients and distributed delivery teams.
• Understanding of AI model governance, including explainability, auditability, and data privacy in production environments.
About SymphonyAI
SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth verticals, including retail, consumer packaged goods, financial services, manufacturing, media, and business IT. SymphonyAI verticals have many leading enterprises as clients. Since its founding in 2017, SymphonyAI has grown rapidly to 2,000 talented leaders, data scientists, and other professionals across 35 countries. SymphonyAI is an SAIGroup company, backed by a $1 billion commitment from Dr. Romesh Wadhwani, a successful entrepreneur and philanthropist.
Visit here, for more information about how we hire, what’s in it for you, our culture and values.
#LI-Remote
Stop the endless job search. Our AI finds and applies to the best jobs for you.
Featuring 224,681+ Jobs in Others
Answer easy questions
224,681+ jobs across 15+ categories
Get your best job matches
Only hand-screened, legit jobs
Find a remote job faster
No ads, scams, or junk
“I was the first applicant for a remote marketing position that got listed on the company website the same day I applied. Had an interview within 48 hours!”