101 to 125 of 3,529 Agile-Software-Development Jobs

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

gates to continue, pivot, or stop. Lead PoCs and MVPs Run time-boxed PoCs (2–8 weeks) and MVPs (8–16 weeks) using Agile methods (Scrum or Kanban) with regular demos and retrospectives. Build and lead cross-functional squads including Product Owner, Data Scientists, ML Engineers, Integration Engineers … mindset: frames problems as hypotheses, focuses on measurable impact, and is willing to stop or pivot when evidence is weak. Delivery excellence: strong Agile practices, risk-based planning, and disciplined stage-gates from idea to production. Technical fluency: able to bridge data science, engineering, security, and business stakeholders ...

decision-making skills, with experience delivering large-scale transformation programs. Preferred Qualifications Experience working in large banking/financial institutions. Certifications in Agile/SAFe, PMP, or cloud platforms (AWS/Azure). Experience in modernization of legacy banking applications. Exposure to API gateways, ESB, and integration middleware. ...

cycle (e.g., Cursor, v0) to enhance team productivity and innovation. Essential Experience: Proven experienced leading/mentoring software engineering teams in an Agile Environment Experience using C#/ASP.NET (Core & Framework) Modern JavaScript Frameworks such as Angular (v8+) Solid understanding of relational databases - MySQL is preferred. Expertise ...

possess strong knowledge of application design, microservices architecture, cloud platforms (preferably AWS), and relational databases. Furthermore, you'll need proven experience championing Agile workflows, modern CI/CD practices, and continuous improvement initiatives. Excellent communication skills, the ability to balance technical delivery with team development, and genuine ...

possess strong knowledge of application design, microservices architecture, cloud platforms (preferably AWS), and relational databases. Furthermore, you'll need proven experience championing Agile workflows, modern CI/CD practices, and continuous improvement initiatives. Excellent communication skills, the ability to balance technical delivery with team development, and genuine ...